Data engineer jobs in Milpitas, CA - 10,382 jobs

At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. Technology - Data and Decision Science - Data Engineering - Manager We are looking for a dynamic and experienced Manager of Data Engineering to lead our team in designing and implementing complex cloud analytics solutions with a strong focus on Databricks. The ideal candidate will possess deep technical expertise in data architecture, cloud technologies, and analytics, along with exceptional leadership and client management skills. The opportunity In this role, you will design and build analytics solutions that deliver significant business value. You will collaborate with other data and analytics professionals, management, and stakeholders to ensure that business requirements are translated into effective technical solutions. Key responsibilities include: Understanding and analyzing business requirements to translate them into technical requirements. Designing, building, and operating scalable data architecture and modeling solutions. Staying up to date with the latest trends and emerging technologies to maintain a competitive edge. Key Responsibilities As a Data Engineering Manager, you will play a crucial role in managing and delivering complex technical initiatives. Your time will be spent across various responsibilities, including: Leading workstream delivery and ensuring quality in all processes. Engaging with clients on a daily basis, actively participating in working sessions, and identifying opportunities for additional services. Implementing resource plans and budgets while managing engagement economics. This role offers the opportunity to work in a dynamic environment where you will face challenges that require innovative solutions. You will learn and grow as you guide others and interpret internal and external issues to recommend quality solutions. Travel may be required regularly based on client needs. Skills and attributes for success To thrive in this role, you should possess a blend of technical and interpersonal skills. The following attributes will make a significant impact: Lead the design and development of scalable data engineering solutions using Databricks on cloud platforms (e.g., AWS, Azure, GCP). Oversee the architecture of complex cloud analytics solutions, ensuring alignment with business objectives and best practices. Manage and mentor a team of data engineers, fostering a culture of innovation, collaboration, and continuous improvement. Collaborate with clients to understand their analytics needs and deliver tailored solutions that drive business value. Ensure the quality, integrity, and security of data throughout the data lifecycle, implementing best practices in data governance. Drive end‑to‑end data pipeline development, including data ingestion, transformation, and storage, leveraging Databricks and other cloud services. Communicate effectively with stakeholders, including technical and non‑technical audiences, to convey complex data concepts and project progress. Manage client relationships and expectations, ensuring high levels of satisfaction and engagement. Stay abreast of the latest trends and technologies in data engineering, cloud computing, and analytics. Strong analytical and problem‑solving abilities. Excellent communication skills, with the ability to convey complex information clearly. Proven experience in managing and delivering projects effectively. Ability to build and manage relationships with clients and stakeholders. To qualify for the role, you must have Bachelor's degree in computer science, Engineering, or a related field required; Master's degree preferred. Typically, no less than 4 - 6 years relevant experience in data engineering, with a focus on cloud data solutions and analytics. Proven expertise in Databricks and experience with Spark for big data processing. Strong background in data architecture and design, with experience in building complex cloud analytics solutions. Experience in leading and managing teams, with a focus on mentoring and developing talent. Strong programming skills in languages such as Python, Scala, or SQL. Excellent problem‑solving skills and the ability to work independently and as part of a team. Strong communication and interpersonal skills, with a focus on client management. Required Expertise for Managerial Role Strategic Leadership: Ability to align data engineering initiatives with organizational goals and drive strategic vision. Project Management: Experience in managing multiple projects and teams, ensuring timely delivery and adherence to project scope. Stakeholder Engagement: Proficiency in engaging with various stakeholders, including executives, to understand their needs and present solutions effectively. Change Management: Skills in guiding clients through change processes related to data transformation and technology adoption. Risk Management: Ability to identify potential risks in data projects and develop mitigation strategies. Technical Leadership: Experience in leading technical discussions and making architectural decisions that impact project outcomes. Documentation and Reporting: Proficiency in creating comprehensive documentation and reports to communicate project progress and outcomes to clients. Large-Scale Implementation Programs Enterprise Data Lake Implementation: Led the design and deployment of a cloud-based data lake solution for a Fortune 500 retail client, integrating data from multiple sources (e.g., ERPs, POS systems, e-commerce platforms) to enable advanced analytics and reporting capabilities. Real-Time Analytics Platform: Managed the development of a real-time analytics platform using Databricks for a financial services organization, enabling real-time fraud detection and risk assessment through streaming data ingestion and processing. Data Warehouse Modernization: Oversaw the modernization of a legacy data warehouse to a cloud-native architecture for a healthcare provider, implementing ETL processes with Databricks and improving data accessibility for analytics and reporting. Ideally, you'll also have Experience with advanced data analytics tools and techniques. Familiarity with machine learning concepts and applications. Knowledge of industry trends and best practices in data engineering. Familiarity with cloud platforms (AWS, Azure, GCP) and their data services. Knowledge of data governance and compliance standards. Experience with machine learning frameworks and tools. What we look for We seek individuals who are not only technically proficient but also possess the qualities of top performers, including a strong sense of collaboration, adaptability, and a passion for continuous learning. If you are driven by results and have a desire to make a meaningful impact, we want to hear from you. FY26NATAID What we offer you At EY, we'll develop you with future-focused skills and equip you with world‑class experiences. We'll empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. Learn more. We offer a comprehensive compensation and benefits package where you'll be rewarded based on your performance and recognized for the value you bring to the business. The base salary range for this job in all geographic locations in the US is $125,500 to $230,200. The base salary range for New York City Metro Area, Washington State and California (excluding Sacramento) is $150,700 to $261,600. Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options. Join us in our team‑led and leader‑enabled hybrid model. Our expectation is for most people in external, client serving roles to work together in person 40‑60% of the time over the course of an engagement, project or year. Under our flexible vacation policy, you'll decide how much vacation time you need based on your own personal circumstances. You'll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well‑being. Are you ready to shape your future with confidence? Apply today. EY accepts applications for this position on an on‑going basis. For those living in California, please click here for additional information. EY focuses on high-ethical standards and integrity among its employees and expects all candidates to demonstrate these qualities. EY | Building a better working world EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets. Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow. EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi‑disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories. EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records, in accordance with applicable law. EY is committed to providing reasonable accommodation to qualified individuals with disabilities including veterans with disabilities. If you have a disability and either need assistance applying online or need to request an accommodation during any part of the application process, please call 1-800-EY-HELP3, select Option 2 for candidate related inquiries, then select Option 1 for candidate queries and finally select Option 2 for candidates with an inquiry which will route you to EY's Talent Shared Services Team (TSS) or email the TSS at **************************. #J-18808-Ljbffr

Salary: $200-250k base + RSUs This fast-growing Series E AI SaaS company is redefining how modern engineering teams build and deploy applications. We're expanding our data science organization to accelerate customer success after the initial sale-driving onboarding, retention, expansion, and long-term revenue growth. About the Role As the senior data scientist supporting post-sales teams, you will use advanced analytics, experimentation, and predictive modeling to guide strategy across Customer Success, Account Management, and Renewals. Your insights will help leadership forecast expansion, reduce churn, and identify the levers that unlock sustainable net revenue retention. Key Responsibilities Forecast & Model Growth: Build predictive models for renewal likelihood, expansion potential, churn risk, and customer health scoring. Optimize the Customer Journey: Analyze onboarding flows, product adoption patterns, and usage signals to improve activation, engagement, and time-to-value. Experimentation & Causal Analysis: Design and evaluate experiments (A/B tests, uplift modeling) to measure the impact of onboarding programs, success initiatives, and pricing changes on retention and expansion. Revenue Insights: Partner with Customer Success and Sales to identify high-value accounts, cross-sell opportunities, and early warning signs of churn. Cross-Functional Partnership: Collaborate with Product, RevOps, Finance, and Marketing to align post-sales strategies with company growth goals. Data Infrastructure Collaboration: Work with Analytics Engineering to define data requirements, maintain data quality, and enable self-serve dashboards for Success and Finance teams. Executive Storytelling: Present clear, actionable recommendations to senior leadership that translate complex analysis into strategic decisions. About You Experience: 6+ years in data science or advanced analytics, with a focus on post-sales, customer success, or retention analytics in a B2B SaaS environment. Technical Skills: Expert SQL and proficiency in Python or R for statistical modeling, forecasting, and machine learning. Domain Knowledge: Deep understanding of SaaS metrics such as net revenue retention (NRR), gross churn, expansion ARR, and customer health scoring. Analytical Rigor: Strong background in experimentation design, causal inference, and predictive modeling to inform customer-lifecycle strategy. Communication: Exceptional ability to translate data into compelling narratives for executives and cross-functional stakeholders. Business Impact: Demonstrated success improving onboarding efficiency, retention rates, or expansion revenue through data-driven initiatives.

A cutting-edge AI search engine company in San Francisco is seeking a Data Partnerships specialist to build their data pipeline. The role involves owning the partnerships cycle, making strategic decisions, negotiating contracts, and potentially building a team. Candidates should have experience in contract negotiation and a Juris Doctor degree. This in-person role offers a competitive salary range of $160,000 - $250,000 with above-market equity. #J-18808-Ljbffr

About GoodLeap GoodLeap is a technology company delivering best-in-class financing and software products for sustainable solutions, from solar panels and batteries to energy-efficient HVAC, heat pumps, roofing, windows, and more. Over 1 million homeowners have benefited from our simple, fast, and frictionless technology that makes the adoption of these products more affordable, accessible, and easier to understand. Thousands of professionals deploying home efficiency and solar solutions rely on GoodLeap's proprietary, AI-powered applications and developer tools to drive more transparent customer communication, deeper business intelligence, and streamlined payment and operations. Our platform has led to more than $30 billion in financing for sustainable solutions since 2018. GoodLeap is also proud to support our award-winning nonprofit, GivePower, which is building and deploying life-saving water and clean electricity systems, changing the lives of more than 1.6 million people across Africa, Asia, and South America. Position Summary The GoodLeap team is looking for a hands‑on Data Engineer with a strong background in API data integrations, Spark processing and data lake development. The focus of this role will be on ingesting production energy data and helping get the aggregated metrics to the many teams in GoodLeap that need them. The successful candidate is a highly motivated individual with strong technical skills to create secure and performant data pipelines as well as support our foundational enterprise data warehouse. The ideal candidate is passionate about quality and has a bold, visionary approach to data practices in a modern finance enterprise. The candidate in this role will be required to work closely with cross‑functional teams to effectively coordinate the complex interdependencies inherent in the applications. Typical teams we collaborate with are Analytics & Reporting, Origination Platform engineers and AI developers. We are looking for a hardworking and passionate engineer who wants to make a difference with the tools they develop. Essential Job Duties and Responsibilities Implement data integrations across the organization as well as with business applications Develop and maintain data oriented web applications with scalable web services Participate in the design and development of projects, either independently or in a team Utilize agile software development lifecycle and DevOps principles Be the data stewards of the organization upholding quality and availability standards for our downstream consumers Be self‑sufficient and fully own the responsibility of executing projects from inception to delivery Provide mentorship to team members including pair programming and skills development Participate in data design and architecture discussions, considering solutions in the context of the larger GoodLeap ecosystem Required Skills, Knowledge & Abilities 6-10 years of full‑time Data Analysis and/or Software Development experience Experience with an end to end reporting & analytics technology: data warehousing (SQL, NoSQL) to BI/Visualization (Tableau, PowerBI, Excel) Degree in Computer Science or related discipline Experience with DataBricks/Spark processing Expertise with relational databases (including functional SQL/stored procedures) and non‑relational databases (MongoDB, DynamoDB, Elastic Search) Experience with orchestrating data pipelines with modern tools such as Airflow Strong knowledge and hands‑on experience with open source web frameworks (e.g. Vue /React) Solid understanding of performance implications and scalability of code Experience with Amazon Web Services (IAM, Cognito, EC2, S3, RDS, Cloud Formation) Experience with messaging paradigms and serverless technologies (Lambda, SQS, SNS, SES) Experience working with server‑less applications on public clouds (e.g. AWS) Experience with large, complex codebases and know how to maintain them $160,000 - $210,000 a year In addition to the above salary, this role may be eligible for a bonus and equity. Additional Information Regarding Job Duties and s Job duties include additional responsibilities as assigned by one's supervisor or other managers related to the position/department. This job description is meant to describe the general nature and level of work being performed; it is not intended to be construed as an exhaustive list of all responsibilities, duties and other skills required for the position. The Company reserves the right at any time with or without notice to alter or change job responsibilities, reassign or transfer job position or assign additional job responsibilities, subject to applicable law. The Company shall provide reasonable accommodations of known disabilities to enable a qualified applicant or employee to apply for employment, perform the essential functions of the job, or enjoy the benefits and privileges of employment as required by the law. If you are an extraordinary professional who thrives in a collaborative work culture and values a rewarding career, then we want to work with you! Apply today! We are committed to protecting your privacy. To learn more about how we collect, use, and safeguard your personal information during the application process, please review our Employment Privacy Policy and Recruiting Policy on AI. #J-18808-Ljbffr

An innovative tech firm in Berkeley seeks a Senior Data Engineer to manage complex data engineering pipelines. You will ensure data quality, support ML engineers across locations, and establish infrastructure standards. The ideal candidate has over 5 years of experience in Data Science or MLOps, strong algorithmic skills, and proficiency in GCP, Python, and SQL. This role offers competitive salary and the chance to impact a growing team in a dynamic field. #J-18808-Ljbffr

A leading AI technology company based in Palo Alto, CA is seeking a Machine Learning Data Engineer. You will build and optimize the data infrastructure for our machine learning systems while collaborating with ML engineers and infrastructure teams. The ideal candidate has a strong engineering background in Python, experience in production data pipelines, and a deep understanding of distributed systems. This role offers comprehensive benefits, a collaborative environment, and opportunities for innovative contributions. #J-18808-Ljbffr

At Gilead, we're creating a healthier world for all people. For more than 35 years, we've tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer - working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world's biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference. Every member of Gilead's team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we're looking for the next wave of passionate and ambitious people ready to make a direct impact. We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together. Gilead's AI Research Center(ARC) is looking for a Principal Data Scientist to spearhead the adoption of AI/ML and transform our clinical development processes. This is a pivotal role where you will provide key thought leadership and drive our strategic vision for advanced analytics, with the goal of optimizing clinical trials, enhancing data-driven decision-making, and providing support for Real-World Evidence (RWE), Clinical Pharmacology, and Biomarkers initiatives. You will be a thought leader in applying AI/ML to real-world clinical challenges, taking deep involvement in all stages of technical development-from coding and configuring compute environments to model evaluation, review, and architecture design. You'll work closely with a variety of cross-functional teams, including architects, data engineers, and product managers, to scope, develop, and operationalize our AI-driven applications, with a specific focus on leveraging AI/ML to advance insights within RWE, Clinical Pharmacology, and Biomarkers. Responsibilities: Innovate and Strategize: Spearhead the strategic vision for leveraging AI/ML within clinical development. You'll partner with cross-functional leaders to identify high-impact opportunities and design innovative solutions that transform how we conduct trials and make data-driven decisions. Lead with Expertise: Guide the full lifecycle of machine learning models from initial concept to real-world application. This includes architecting scalable solutions, hands-on algorithm development, and ensuring models are rigorously evaluated and operationalized for use in RWE, Clinical Pharmacology, and Biomarkers. Mentor and Empower: Act as a force multiplier for our data science team. You'll coach and mentor senior and junior data scientists, fostering a culture of technical excellence and continuous learning. Translate and Execute: Serve as a bridge between technical teams and business stakeholders. You'll translate complex business challenges into precise data science problems and, in a product manager-like role, drive the development of these solutions from proof-of-concept to production. Drive Breakthroughs: Research and develop cutting-edge algorithms to solve critical challenges. This could involve using NLP for patient insights, computer vision for biomarker analysis, or predictive models to optimize trial logistics. You'll be at the forefront of applying these techniques in a biotech context. Build the Foundation: Design and implement the technical and process building blocks needed to scale our AI/ML capabilities. This includes working with IT partners to curate and operationalize the datasets essential for fueling our analytical pipelines. Influence and Advise: Interface directly with internal stakeholders, acting as a trusted advisor to help them understand the potential of advanced analytics and apply data-driven approaches to optimize clinical trial operations. Stay Ahead: Continuously monitor the landscape of machine learning and biopharmaceutical innovation. You'll ensure our team is leveraging the latest state-of-the-art techniques to maintain a competitive edge. Technical Skills: Advanced Model Development & Operationalization: Deep expertise in developing, deploying, and managing complex machine learning and deep learning algorithms at scale. This includes a profound understanding of model evaluation, scoring methodologies, and mitigation of model bias to ensure robust, ethical, and reliable outcomes. Data & Computational Proficiency: Fluent in Python or R and SQL, with hands-on experience in building and optimizing data pipelines for analytical and model development purposes. Cloud-Native AI/ML: Demonstrated experience with Cloud DevOps on AWS as it pertains to the entire data science lifecycle, from data ingestion to model serving and monitoring. Translational Research: Proven ability to translate foundational AI/ML research into functional, production-ready packages and applications that directly support strategic initiatives in areas like RWE, Clinical Pharmacology, and Biomarkers. Basic Qualifications: Doctorate and 5+ years of relevant experience OR Master's and 8+ years of relevant experience OR Bachelor's and 10+ years of relevant experience Preferred Qualifications: Ability to translate stakeholder needs into clear technical requirements, including those related to RWE, Clinical Pharmacology, and Biomarkers. Skill in scoping project requirements and developing timelines. Knowledge of product management principles. Experience with code management using Git. Strong technical documentation skills. Join us at the AI Research Center to shape the future of clinical development with groundbreaking AI/ML solutions, and contribute to advancements in RWE, Clinical Pharmacology, and Biomarkers! The salary range for this position is: Bay Area: $210,375.00 - $272,250.00.Other US Locations: $191,250.00 - $247,500.00. At Gilead, we're creating a healthier world for all people. For more than 35 years, we've tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer - working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world's biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference. Every member of Gilead's team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we're looking for the next wave of passionate and ambitious people ready to make a direct impact. We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together. Job Description Gilead's AI Research Center(ARC) is looking for a Principal Data Scientist to spearhead the adoption of AI/ML and transform our clinical development processes. This is a pivotal role where you will provide key thought leadership and drive our strategic vision for advanced analytics, with the goal of optimizing clinical trials, enhancing data-driven decision-making, and providing support for Real-World Evidence (RWE), Clinical Pharmacology, and Biomarkers initiatives. You will be a thought leader in applying AI/ML to real-world clinical challenges, taking deep involvement in all stages of technical development-from coding and configuring compute environments to model evaluation, review, and architecture design. You'll work closely with a variety of cross-functional teams, including architects, data engineers, and product managers, to scope, develop, and operationalize our AI-driven applications, with a specific focus on leveraging AI/ML to advance insights within RWE, Clinical Pharmacology, and Biomarkers. Responsibilities: Innovate and Strategize: Spearhead the strategic vision for leveraging AI/ML within clinical development. You'll partner with cross-functional leaders to identify high-impact opportunities and design innovative solutions that transform how we conduct trials and make data-driven decisions. Lead with Expertise: Guide the full lifecycle of machine learning models from initial concept to real-world application. This includes architecting scalable solutions, hands-on algorithm development, and ensuring models are rigorously evaluated and operationalized for use in RWE, Clinical Pharmacology, and Biomarkers. Mentor and Empower: Act as a force multiplier for our data science team. You'll coach and mentor senior and junior data scientists, fostering a culture of technical excellence and continuous learning. Translate and Execute: Serve as a bridge between technical teams and business stakeholders. You'll translate complex business challenges into precise data science problems and, in a product manager-like role, drive the development of these solutions from proof-of-concept to production. Drive Breakthroughs: Research and develop cutting-edge algorithms to solve critical challenges. This could involve using NLP for patient insights, computer vision for biomarker analysis, or predictive models to optimize trial logistics. You'll be at the forefront of applying these techniques in a biotech context. Build the Foundation: Design and implement the technical and process building blocks needed to scale our AI/ML capabilities. This includes working with IT partners to curate and operationalize the datasets essential for fueling our analytical pipelines. Influence and Advise: Interface directly with internal stakeholders, acting as a trusted advisor to help them understand the potential of advanced analytics and apply data-driven approaches to optimize clinical trial operations. Stay Ahead: Continuously monitor the landscape of machine learning and biopharmaceutical innovation. You'll ensure our team is leveraging the latest state-of-the-art techniques to maintain a competitive edge. Technical Skills: Advanced Model Development & Operationalization: Deep expertise in developing, deploying, and managing complex machine learning and deep learning algorithms at scale. This includes a profound understanding of model evaluation, scoring methodologies, and mitigation of model bias to ensure robust, ethical, and reliable outcomes. Data & Computational Proficiency: Fluent in Python or R and SQL, with hands-on experience in building and optimizing data pipelines for analytical and model development purposes. Cloud-Native AI/ML: Demonstrated experience with Cloud DevOps on AWS as it pertains to the entire data science lifecycle, from data ingestion to model serving and monitoring. Translational Research: Proven ability to translate foundational AI/ML research into functional, production-ready packages and applications that directly support strategic initiatives in areas like RWE, Clinical Pharmacology, and Biomarkers. Basic Qualifications: Doctorate and 5+ years of relevant experience OR Master's and 8+ years of relevant experience OR Bachelor's and 10+ years of relevant experience Preferred Qualifications: Ability to translate stakeholder needs into clear technical requirements, including those related to RWE, Clinical Pharmacology, and Biomarkers. Skill in scoping project requirements and developing timelines. Knowledge of product management principles. Experience with code management using Git. Strong technical documentation skills. Join us at the AI Research Center to shape the future of clinical development with groundbreaking AI/ML solutions, and contribute to advancements in RWE, Clinical Pharmacology, and Biomarkers! The salary range for this position is: Bay Area: $210,375.00 - $272,250.00.Other US Locations: $191,250.00 - $247,500.00. Gilead considers a variety of factors when determining base compensation, including experience, qualifications, and geographic location. These considerations mean actual compensation will vary. This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package. Benefits include company-sponsored medical, dental, vision, and life insurance plans*. For additional benefits information, visit: ****************************************************************** * Eligible employees may participate in benefit plans, subject to the terms and conditions of the applicable plans. For jobs in the United States: Gilead Sciences Inc. is committed to providing equal employment opportunities to all employees and applicants for employment, and is dedicated to fostering an inclusive work environment comprised of diverse perspectives, backgrounds, and experiences. Employment decisions regarding recruitment and selection will be made without discrimination based on race, color, religion, national origin, sex , age, sexual orientation, physical or mental disability, genetic information or characteristic, gender identity and expression, veteran status, or other non-job related characteristics or other prohibited grounds specified in applicable federal, state and local laws. In order to ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Era Veterans' Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact ApplicantAccommodations@gilead.com for assistance. For more information about equal employment opportunity protections, please view the 'Know Your Rights' poster. NOTICE: EMPLOYEE POLYGRAPH PROTECTION ACT YOUR RIGHTS UNDER THE FAMILY AND MEDICAL LEAVE ACT PAY TRANSPARENCY NONDISCRIMINATION PROVISION Our environment respects individual differences and recognizes each employee as an integral member of our company. Our workforce reflects these values and celebrates the individuals who make up our growing team. Gilead provides a work environment free of harassment and prohibited conduct. We promote and support individual differences and diversity of thoughts and opinion. For Current Gilead Employees and Contractors: Please apply via the Internal Career Opportunities portal in Workday. Share: Job Requisition ID R0046852 Full Time/Part Time Full-Time Job Level Associate Director Click below to return to the Gilead Careers site Click below to see a list of upcoming events Click below to return to the Kite, a Gilead company Careers site #J-18808-Ljbffr

A pioneering audio tech company based in San Francisco is searching for a Founding Machine Learning Infrastructure Engineer. In this role, you will build and scale the core infrastructure that powers cutting-edge audio ML products. You will lead the development of systems for training and deploying models. Candidates should have over 5 years of backend experience with strong skills in cloud infrastructure and machine learning principles. The company offers benefits like unlimited PTO and comprehensive health coverage. #J-18808-Ljbffr

About us At Eon, we are at the forefront of large-scale neuroscientific data collection. Our mission is to enable the safe and scalable development of brain emulation technology to empower humanity over the next decade, beginning with the creation of a fully emulated digital twin of a mouse. Role We're a San Francisco team collecting very large microscopy datasets and we need an expert to design and implement our end-to-end data pipeline, from high-rate ingest to multi-petabyte storage and downstream processing. You'll own the strategy (on-prem vs. S3 or hybrid), the bill of materials, and the deployment, and you'll be on the floor wiring, racking, tuning, and validating performance. Our current instruments generate data at ~1+ GB/s sustained (higher during bursts) and the program will accumulate multiple petabyes total over time. You'll help us choose and implement the right architecture considering reliability and cost controls. Outcomes (what success looks like) Within 2 weeks: Implement an immediate data-handling strategy that reliably ingests our initial data streams. Within 2 weeks: Deliver a documented medium-term data architecture covering storage, networking, ingest, and durability. Within 1 month: Operationalize the medium-term pipeline in production (ingest → buffer → long-term store → compute access). Ongoing: Maintain ≥95% uptime for the end-to-end data-handling pipeline after setup. Responsibilities Architect ingest & storage: Choose and implement an on-prem hardware and data pipeline design or a cloud/S3 alternative with explicit cost and performance tradeoffs at multi-petabyte scale. Set up a sustained-write ingest path ≥1 GB/s with adequate burst headroom (camera/frame-to-disk), including networking considerations, cooling, and throttling safeguards. Optimize footprint & cost: Incorporate on-the-fly compression/downsampling options and quantify CPU budget vs. write-speed tradeoffs; document when/where to compress to control $/PB. Integrate with acquisition workflows ensuring image data and metadata are compatible with downstream stitching/flat-field correction pipelines. Enable downstream compute: Expose the data to segmentation/analysis stacks (local GPU nodes or cloud). Skills 5+ years designing and deploying high-throughput storage or HPC pipelines (≥1 GB/s sustained ingest) in production. Deep hands-on with: NVMe RAID/striping, ZFS/MDRAID/erasure coding, PCIe topology, NUMA pinning, Linux performance tuning, and NIC offload features. Proven delivery of multi-GB/s ingest systems and petabyte-scale storage in production (life-sciences, vision, HPC, or media). Experience building tiered storage systems (NVMe → HDD/object) and validating real-world throughput under sustained load. Practical S3/object-storage know-how (AWS S3 and/or on-prem S3-compatible systems) with lifecycle, versioning, and cost controls. Data integrity & reliability: snapshots, scrubs, replication, erasure coding, and backup/DR for PB-scale systems. Networking: ****25/40/100 GbE (SFP+/SFP28), RDMA/ RoCE/iWARP familiarity; switch config and path tuning. Ability to spec and rack hardware: selecting chassis/backplanes, RAID/HBA cards, NICs, and cooling strategies to prevent NVMe throttling under sustained writes. Ideal skills: Experience with microscopy or scientific imaging ingest at frame-to-disk speeds, including Micro-Manager-based pipelines and raw-to-containerized format conversions. Experience with life science imaging data a plus. Engagement details Contract (1099 or corp-to-corp); contract-to-hire if there's a mutual fit. On-site requirement: You must be physically present in San Francisco during build-out and initial operations; local field work (e.g., UCSF) as needed. Compensation: Contract, $100-300/hour Timeline: Immediate start #J-18808-Ljbffr

A leading technology company in San Francisco is seeking a Machine Learning Engineer to ensure the quality and coverage of data across diverse languages. You will design large-scale datasets, evaluate models, and implement quality control systems. The ideal candidate has expertise in multilingual datasets and a strong background in applied ML. This full-time role offers competitive benefits, including fully covered insurance and in-office perks, in a supportive team environment. #J-18808-Ljbffr

Employment Type Full time Department Engineering About us At Eon, we are at the forefront of large-scale neuroscientific data collection. Our mission is to enable the safe and scalable development of brain emulation technology to empower humanity over the next decade, beginning with the creation of a fully emulated digital twin of a mouse. Role We're a San Francisco team collecting very large microscopy datasets and we need an expert to design and implement our end-to-end data pipeline, from high-rate ingest to multi-petabyte storage and downstream processing. You'll own the strategy (on-prem vs. S3 or hybrid), the bill of materials, and the deployment, and you'll be on the floor wiring, racking, tuning, and validating performance. Our current instruments generate data at ~1+ GB/s sustained (higher during bursts) and the program will accumulate multiple petabyes total over time. You'll help us choose and implement the right architecture considering reliability and cost controls. Outcomes (what success looks like) Within 2 weeks: Implement an immediate data-handling strategy that reliably ingests our initial data streams. Within 2 weeks: Deliver a documented medium-term data architecture covering storage, networking, ingest, and durability. Within 1 month: Operationalize the medium-term pipeline in production (ingest → buffer → long-term store → compute access). Ongoing: Maintain ≥95% uptime for the end-to-end data-handling pipeline after setup. Responsibilities Architect ingest & storage: Choose and implement an on-prem hardware and data pipeline design or a cloud/S3 alternative with explicit cost and performance tradeoffs at multi-petabyte scale. Set up a sustained-write ingest path ≥1 GB/s with adequate burst headroom (camera/frame-to-disk), including networking considerations, cooling, and throttling safeguards. Optimize footprint & cost: Incorporate on-the-fly compression/downsampling options and quantify CPU budget vs. write-speed tradeoffs; document when/where to compress to control $/PB. Integrate with acquisition workflows ensuring image data and metadata are compatible with downstream stitching/flat-field correction pipelines. Enable downstream compute: Expose the data to segmentation/analysis stacks (local GPU nodes or cloud). Skills 5+ years designing and deploying high-throughput storage or HPC pipelines (≥1 GB/s sustained ingest) in production. Deep hands-on with: NVMe RAID/striping, ZFS/MDRAID/erasure coding, PCIe topology, NUMA pinning, Linux performance tuning, and NIC offload features. Proven delivery of multi-GB/s ingest systems and petabyte-scale storage in production (life-sciences, vision, HPC, or media). Experience building tiered storage systems (NVMe ← HDD/object) and validating real-world throughput under sustained load. Practical S3/object-storage know-how (AWS S3 and/or on-prem S3-compatible systems) with lifecycle, versioning, and cost controls. Data integrity & reliability: snapshots, scrubs, replication, erasure coding, and backup/DR for PB-scale systems. Networking: ****25/40/100 GbE (SFP+/SFP28), RDMA/ RoCE/iWARP familiarity; switch config and path tuning. Ability to spec and rack hardware: selecting chassis/backplanes, RAID/HBA cards, NICs, and cooling strategies to prevent NVMe throttling under sustained writes. Ideal skills: Experience with microscopy or scientific imaging ingest at frame-to-disk speeds, including Micro-Manager-based pipelines and raw-to-containerized format conversions. Experience with life science imaging data a plus. Engagement details Contract (1099 or corp-to-corp); contract-to-hire if there's a mutual fit. On-site requirement: You must be physically present in San Francisco during build-out and initial operations; local field work (e.g., UCSF) as needed. Compensation: Contract, $100-300/hour Timeline: Immediate start #J-18808-Ljbffr

Mechanical design, the work done in CAD, is the rate-limiter for progress in the physical world. However, there are only 2-4 million people on Earth who know how to CAD. But what if hundreds of millions could? What if creating something in the real world were as easy as imagining the use case, or sketching it on paper? Backflip is building a foundation model for mechanical design: unifying the world's scattered engineering knowledge into an intelligent, end-to-end design environment. Our goal is to enable anyone to imagine a solution and hit “print.” Founded by a second-time CEO in the same space (first company: Markforged), Backflip combines deep industry insight with breakthrough AI research. Backed by a16z and NEA, we raised a $30M Series A and built a deeply technical, mission-driven team. We're building the AI foundation that tomorrow's space elevators, nanobots, and spaceships will be built in. If you're excited to define the next generation of hard tech, come build it with us. The Role We're looking for a Staff Machine Learning Data Engineer to lead and build the data pipelines powering Backflip's foundation model for manufacturing and CAD. You'll design the systems, tools, and strategies that turn the world's engineering knowledge - text, geometry, and design intent - into high-quality training data. This is a core leadership role within the AI team, driving the data architecture, augmentation, and evaluation that underpin our model's performance and evolution. You'll collaborate with Machine Learning Engineers to run data-driven experiments, analyze results, and deliver AI products that shape the future of the physical world. What You'll Do Architect and own Backflip's ML data pipeline, from ingestion to processing to evaluation. Define data strategy: establish best practices for data augmentation, filtering, and sampling at scale. Design scalable data systems for multimodal training (text, geometry, CAD, and more). Develop and automate data collection, curation, and validation workflows. Collaborate with MLEs to design and execute experiments that measure and improve model performance. Build tools and metrics for dataset analysis, monitoring, and quality assurance. Contribute to model development through insights grounded in data, shaping what, how, and when we train. Who You Are You've built and maintained ML data pipelines at scale, ideally for foundation or generative models, that shipped into production in the real world. You have deep experience with data engineering for ML, including distributed systems, data extraction, transformation, and loading, and large-scale data processing (e.g. PySpark, Beam, Ray, or similar). You're fluent in Python and experienced with ML frameworks and data formats (Parquet, TFRecord, HuggingFace datasets, etc.). You've developed data augmentation, sampling, or curation strategies that improved model performance. You think like both an engineer and an experimentalist: curious, analytical, and grounded in evidence. You collaborate well across AI development, infra, and product, and enjoy building the data systems that make great models possible. You care deeply about data quality, reproducibility, and scalability. You're excited to help shape the future of AI for physical design. Bonus points if: You are comfortable working with a variety of complex data formats, e.g. for 3D geometry kernels or rendering engines. You have an interest in math, geometry, topology, rendering, or computational geometry. You've worked in 3D printing, CAD, or computer graphics domains. Why Backflip This is a rare opportunity to own the data backbone of a frontier foundation model, and help define how AI learns to design the physical world. You'll join a world-class, mission-driven team operating at the intersection of research, engineering, and deep product sense, building systems that let people design the physical world as easily as they imagine it. Your work will directly shape the performance, capability, and impact of Backflip's foundation model, the core of how the world will build in the future. Let's build the tools the future will be made in. #J-18808-Ljbffr

A financial services company in San Francisco seeks a Distinguished Data Engineer to lead innovation in data architecture and management. The role involves building critical data solutions, mentoring teams, and leveraging cloud technologies like AWS. Ideal candidates will have significant experience in data engineering, a Bachelor's degree, and proficiency in modern data practices to drive customer value through analytics and automation. #J-18808-Ljbffr

A leading security technology firm in California is seeking a skilled Data Science Engineer. You will harness the power of unsupervised machine learning to detect fraudulent activities across various sectors. Ideal candidates have experience with Java/C++, data structures, and machine learning. The company offers competitive pay, flexible schedules, equity participation, health benefits, a collaborative environment, and unique perks such as catered lunches and game nights. #J-18808-Ljbffr

A growing technology firm based in San Francisco is seeking a Demand Generation Marketer to drive campaigns that turn prospects into lifelong customers. This role emphasizes creativity in marketing, collaboration with teams, and a strong data-driven mindset. The ideal candidate will have experience in B2B SaaS environments and a passion for engaging technical audiences. Flexible work environment and competitive compensation offered. #J-18808-Ljbffr

A leading technology company located in San Jose is seeking an engineer specialized in FPGA build flows and software automation. The candidate will own FPGA compile/build processes, develop robust regression pipelines, and ensure quality throughout the design and validation phases. An ideal candidate will possess strong experience in toolchain validation and collaboration across teams. This position offers an innovative environment focused on advancing technology and collaboration within a diverse team. #J-18808-Ljbffr

PG Forsta is the leading experience measurement, data analytics, and insights provider for complex industries-a status we earned over decades of deep partnership with clients to help them understand and meet the needs of their key stakeholders. Our earliest roots are in U.S. healthcare -perhaps the most complex of all industries. Today we serve clients around the globe in every industry to help them improve the Human Experiences at the heart of their business. We serve our clients through an unparalleled offering that combines technology, data, and expertise to enable them to pinpoint and prioritize opportunities, accelerate improvement efforts and build lifetime loyalty among their customers and employees. Like all great companies, our success is a function of our people and our culture. Our employees have world-class talent, a collaborative work ethic, and a passion for the work that have earned us trusted advisor status among the world's most recognized brands. As a member of the team, you will help us create value for our clients, you will make us better through your contribution to the work and your voice in the process. Ours is a path of learning and continuous improvement; team efforts chart the course for corporate success. Our Mission: We empower organizations to deliver the best experiences. With industry expertise and technology, we turn data into insights that drive innovation and action. Our Values: To put Human Experience at the heart of organizations so every person can be seen and understood. Energize the customer relationship:Our clients are our partners. We make their goals our own, working side by side to turn challenges into solutions. Success starts with me:Personal ownership fuels collective success. We each play our part and empower our teammates to do the same. Commit to learning:Every win is a springboard. Every hurdle is a lesson. We use each experience as an opportunity to grow. Dare to innovate:We challenge the status quo with creativity and innovation as our true north. Better together:We check our egos at the door. We work together, so we win together. We are seeking an experienced Staff Data Engineer to join our Unified Data Platform team. The ideal candidate will design, develop, and maintain enterprise-scale data infrastructure leveraging Azure and Databricks technologies. This role involves building robust data pipelines, optimizing data workflows, and ensuring data quality and governance across the platform. You will collaborate closely with analytics, data science, and business teams to enable data-driven decision-making. Duties & Responsibilities: Design, build, and optimizedata pipelinesand workflows in AzureandDatabricks, including Data Lake and SQL Database integrations. Implement scalable ETL/ELT frameworksusing Azure Data Factory,Databricks, and Spark. Optimize data structures and queries for performance, reliability, and cost efficiency. Drivedata quality and governance initiatives, including metadata management and validation frameworks. Collaborate with cross-functional teams to define and implementdata modelsaligned with business and analytical requirements. Maintain clear documentation and enforce engineering best practices for reproducibility and maintainability. Ensure adherence tosecurity, compliance, and data privacystandards. Mentor junior engineers and contribute to establishingengineering best practices. SupportCI/CD pipeline developmentfor data workflows using GitLab or Azure DevOps. Partner with data consumers to publish curated datasets into reporting tools such as Power BI. Stay current with advancements in Azure, Databricks, Delta Lake, and data architecture trends. Technical Skills: Advanced proficiency in Azure 5+ years(Data Lake, ADF, SQL). Strong expertise in Databricks (5+ years),Apache Spark (5+ years), and Delta Lake (5+ years). Proficient in SQL (10+ years)and Python (5+ years); familiarity with Scalais a plus. Strong understanding ofdata modeling,data governance, andmetadata management. Knowledge ofsource control (Git),CI/CD, and modern DevOps practices. Familiarity with Power BIvisualization tool. Minimum Qualifications: Bachelor's or Master's degree in Computer Science, Data Science, or related field. 7+ yearsof experience in data engineering, with significant hands-on work incloud-based data platforms (Azure). Experience buildingreal-time data pipelinesand streaming frameworks. Strong analytical and problem-solving skills. Proven ability tolead projectsand mentor engineers. Excellent communication and collaboration skills. Preferred Qualifications: Master's degree in Computer Science, Engineering, or a related field. Exposure tomachine learning integrationwithin data engineering pipelines. Don't meet every single requirement?Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. At PG Forsta we are dedicated to building a diverse, inclusive and authentic workplace, so if you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. Additional Information for US based jobs: Press Ganey Associates LLC is an Equal Employment Opportunity/Affirmative Action employer and well committed to a diverse workforce. We do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, veteran status, and basis of disability or any other federal, state, or local protected class. Pay Transparency Non-Discrimination Notice - Press Ganey will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information. The expected base salary for this position ranges from $110,000 to $170,000. It is not typical for offers to be made at or near the top of the range. Salary offers are based on a wide range of factors including relevant skills, training, experience, education, and, where applicable, licensure or certifications obtained. Market and organizational factors are also considered. In addition to base salary and a competitive benefits package, successful candidates are eligible to receive a discretionary bonus or commission tied to achieved results. All your information will be kept confidential according to EEO guidelines. Our privacy policy can be found here:legal-privacy/

Salary: $200-250k base + RSUs This fast-growing Series E AI SaaS company is redefining how modern engineering teams build and deploy applications. We're expanding our data science organization to accelerate customer success after the initial sale-driving onboarding, retention, expansion, and long-term revenue growth. About the Role As the senior data scientist supporting post-sales teams, you will use advanced analytics, experimentation, and predictive modeling to guide strategy across Customer Success, Account Management, and Renewals. Your insights will help leadership forecast expansion, reduce churn, and identify the levers that unlock sustainable net revenue retention. Key Responsibilities Forecast & Model Growth: Build predictive models for renewal likelihood, expansion potential, churn risk, and customer health scoring. Optimize the Customer Journey: Analyze onboarding flows, product adoption patterns, and usage signals to improve activation, engagement, and time-to-value. Experimentation & Causal Analysis: Design and evaluate experiments (A/B tests, uplift modeling) to measure the impact of onboarding programs, success initiatives, and pricing changes on retention and expansion. Revenue Insights: Partner with Customer Success and Sales to identify high-value accounts, cross-sell opportunities, and early warning signs of churn. Cross-Functional Partnership: Collaborate with Product, RevOps, Finance, and Marketing to align post-sales strategies with company growth goals. Data Infrastructure Collaboration: Work with Analytics Engineering to define data requirements, maintain data quality, and enable self-serve dashboards for Success and Finance teams. Executive Storytelling: Present clear, actionable recommendations to senior leadership that translate complex analysis into strategic decisions. About You Experience: 6+ years in data science or advanced analytics, with a focus on post-sales, customer success, or retention analytics in a B2B SaaS environment. Technical Skills: Expert SQL and proficiency in Python or R for statistical modeling, forecasting, and machine learning. Domain Knowledge: Deep understanding of SaaS metrics such as net revenue retention (NRR), gross churn, expansion ARR, and customer health scoring. Analytical Rigor: Strong background in experimentation design, causal inference, and predictive modeling to inform customer-lifecycle strategy. Communication: Exceptional ability to translate data into compelling narratives for executives and cross-functional stakeholders. Business Impact: Demonstrated success improving onboarding efficiency, retention rates, or expansion revenue through data-driven initiatives.

Zyphra is an artificial intelligence company based in Palo Alto, California. The Role: As a Machine Learning Data Engineer - Systems & Retrieval, you will build and optimize the data infrastructure that fuels our machine learning systems. This includes designing high-performance pipelines for collecting, transforming, indexing, and serving massive, heterogeneous datasets from raw web-scale data to enterprise document corpora. You'll play a central role in architecting retrieval systems for LLMs and enabling scalable training and inference with clean, accessible, and secure data. You'll have an impact across both research and product teams by shaping the foundation upon which intelligent systems are trained, retrieved, and reasoned over. You'll work across: Design and implementation of distributed data ingestion and transformation pipelines Building retrieval and indexing systems that support RAG and other LLM-based methods Mining and organizing large unstructured datasets, both in research and production environments Collaborating with ML engineers, systems engineers, and DevOps to scale pipelines and observability Ensuring compliance and access control in data handling, with security and auditability in mind Requirements: Strong software engineering background with fluency in Python Experience designing, building, and maintaining data pipelines in production environments Deep understanding of data structures, storage formats, and distributed data systems Familiarity with indexing and retrieval techniques for large-scale document corpora Understanding of database systems (SQL and NoSQL), their internals, and performance characteristics Strong attention to security, access controls, and compliance best practices (e.g., GDPR, SOC2) Excellent debugging, observability, and logging practices to support reliability at scale Strong communication skills and experience collaborating across ML, infra, and product teams Bonus Skill Set: Experience building or maintaining LLM-integrated retrieval systems (e.g, RAG pipelines) Academic or industry background in data mining, search, recommendation systems, or IR literature Experience with large-scale ETL systems and tools like Apache Beam, Spark, or similar Familiarity with vector databases (e.g., FAISS, Weaviate, Pinecone) and embedding-based retrieval Understanding of data validation and quality assurance in machine learning workflows Experience working on cross-functional infra and MLOps teams Knowledge of how data infrastructure supports training pipelines, inference serving, and feedback loops Comfort working across raw, unstructured data, structured databases, and model-ready formats Why Work at Zyphra: Our research methodology is to make grounded, methodical steps toward ambitious goals. Both deep research and engineering excellence are equally valued We strongly value new and crazy ideas and are very willing to bet big on new ideas We move as quickly as we can; we aim to minimize the bar to impact as low as possible We all enjoy what we do and love discussing AI Benefits and Perks: Comprehensive medical, dental, vision, and FSA plans Competitive compensation and 401(k) Relocation and immigration support on a case-by-case basis On-site meals prepared by a dedicated culinary team; Thursday Happy Hours In-person team in Palo Alto, CA, with a collaborative, high-energy environment If you're excited by the challenge of high-scale, high-performance data engineering in the context of cutting-edge AI, you'll thrive in this role. Apply Today! #J-18808-Ljbffr