Databricks Data Engineer - Manager - Consulting - Location Open
Ernst & Young Oman 4.7
Data engineer job in San Francisco, CA
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 - DataEngineering - Manager
We are looking for a dynamic and experienced Manager of DataEngineering 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 DataEngineering 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 dataengineering 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 dataengineers, 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 dataengineering, 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 dataengineering, 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 dataengineering 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 dataengineering.
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.
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 **************************.
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$150.7k-261.6k yearly 3d ago
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Full-Stack Engineer: AI Data Editor
Hex 3.9
Data engineer job in San Francisco, CA
A cutting-edge data analytics firm in San Francisco is seeking a full-stack engineer to enhance user experiences and integrate AI tools within their platform. You will work on innovative projects that shape data interactions, collaborate with teams on product initiatives, and tackle UX challenges. Ideal candidates should possess 3+ years of software engineering experience, proficiency in React and Typescript, and a strong desire to work in AI development. This position offers a competitive salary and benefits, with a hybrid work model.
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$126k-178k yearly est. 4d ago
Staff Data Scientist - Sales Analytics
Harnham
Data engineer job in Santa Rosa, CA
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 looking for a Staff Data Scientist to drive Sales and Go-to-Market (GTM) analytics, applying advanced modeling and experimentation to accelerate revenue growth and optimize the full sales funnel.
About the Role
As the senior data scientist supporting Sales and GTM, you will combine statistical modeling, experimentation, and advanced analytics to inform strategy and guide decision-making across our revenue organization. Your work will help leadership understand pipeline health, predict outcomes, and identify the levers that unlock sustainable growth.
Key Responsibilities
Model the Business: Build forecasting and propensity models for pipeline generation, conversion rates, and revenue projections.
Optimize the Sales Funnel: Analyze lead scoring, opportunity progression, and deal velocity to recommend improvements in acquisition, qualification, and close rates.
Experimentation & Causal Analysis: Design and evaluate experiments (A/B tests, uplift modeling) to measure the impact of pricing, incentives, and campaign initiatives.
Advanced Analytics for GTM: Apply machine learning and statistical techniques to segment accounts, predict churn/expansion, and identify high-value prospects.
Cross-Functional Partnership: Work closely with Sales, Marketing, RevOps, and Product to influence GTM strategy and ensure data-driven decisions.
Data Infrastructure Collaboration: Partner with Analytics Engineering to define data requirements, ensure data quality, and enable self-serve reporting.
Strategic Insights: Present findings to executive leadership, translating complex analyses into actionable recommendations.
About You
Experience: 6+ years in data science or advanced analytics roles, with significant time spent in B2B SaaS or developer tools environments.
Technical Depth: Expert in SQL and proficient in Python or R for statistical modeling, forecasting, and machine learning.
Domain Knowledge: Strong understanding of sales analytics, revenue operations, and product-led growth (PLG) motions.
Analytical Rigor: Skilled in experimentation design, causal inference, and building predictive models that influence GTM strategy.
Communication: Exceptional ability to tell a clear story with data and influence senior stakeholders across technical and business teams.
Business Impact: Proven record of driving measurable improvements in pipeline efficiency, conversion rates, or revenue outcomes.
$200k-250k yearly 1d ago
Data Partnerships Lead - Equity & Growth (SF)
Exa
Data engineer job in San Francisco, CA
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.
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$160k-250k yearly 4d ago
Senior Energy Data Engineer - API & Spark Pipelines
Medium 4.0
Data engineer job in San Francisco, CA
A technology finance firm in San Francisco is seeking an experienced DataEngineer. The role involves building data pipelines, integrating data across various platforms, and developing scalable web applications. The ideal candidate will have a strong background in data analysis, software development, and experience with AWS. The salary range for this position is between $160,000 and $210,000, with potential bonuses and equity.
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$160k-210k yearly 2d ago
Senior Data Engineer: ML Pipelines & Signal Processing
Zendar
Data engineer job in Berkeley, CA
An innovative tech firm in Berkeley seeks a Senior DataEngineer to manage complex dataengineering 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.
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$110k-157k yearly est. 2d ago
Data Scientist
Everfit 3.8
Data engineer job in Santa Rosa, CA
Data Scientist Everfit | Hybrid, San Francisco Bay Area
Everfit is a fitness technology company building an AI-powered coaching platform that serves 280,000+ coaches and Millions of training clients globally. We're transforming how fitness professionals deliver personalized training and nutrition guidance to their clients through intelligent automation and data-driven insights.
About the Role
We're looking for a senior data scientist who is passionate about fitness and energized by turning data into actionable insights that help coaches and their clients succeed. You'll play a critical role in understanding user behavior, product performance, and business metrics to inform strategic decisions as we scale our platform.
What You'll Do
Product Analytics & User Insights
Define and track key product metrics (activation, engagement, retention, churn) to measure product health and success.
Conduct cohort, funnel, and retention analyses to uncover behavioral insights and inform feature prioritization.
Identify opportunities to improve onboarding, engagement, and coach-client interactions.
Experimentation & A/B Testing
Own the experimentation framework and guide teams through hypothesis design, sample sizing, execution, and interpretation.
Strategic Impact & Roadmapping
Collaborate with leadership to translate data insights into roadmap priorities and measurable business outcomes.
Build predictive models and scenario analyses to support forecasting, pricing, and product investment decisions.
Establish best practices in data instrumentation, dashboarding, and self-serve analytics across teams.
Technical Foundations
Partner with dataengineering to improve pipelines and instrumentation.
Leverage tools such as SQL, Python/R, data visualization platforms, and experimentation platforms.
Marketing Analytics & Optimization
Analyze customer acquisition funnels and marketing performance to identify high-impact opportunities for growth and conversion.
Partner with marketing and growth teams to design and evaluate campaign experiments
What We're Looking For
4-6 years of experience in a data analyst or analytics role, preferably at a growth-stage tech company
Strong proficiency in SQL and experience setting up data pipelines, transforming data, and analyzing large datasets
Deep experience with creating dashboards and providing analysis on product analytics and data visualization tools (Amplitude, Looker, Tableau, Mode, or similar)
Understanding of SaaS metrics and cohort analysis
Experience with translating numerical findings into clear insights for non-technical team members
Genuine passion for fitness, health, or wellness (we build for coaches so you need to understand their world)
Bonus Points:
Experience with Python or R for statistical analysis
Experience in a PLG (Product-Led Growth) environment
Experience working at a company during a hypergrowth phase
Background in fitness, health, wellness, or coaching industries
You'll thrive here if you:
Are naturally curious and love asking "why" until you find the answer
Are excited by fast-paced, high-growth environments with a passion for building out systems for scaling
Enjoy collaborating with global teams and making complex topics understandable
Are comfortable with ambiguity and can structure your own work
Care deeply about the impact your insights have on real coaches and their clients
Why Join Everfit
Establish the foundations for Fitness Intelligence and help shape the future of coaching for millions around the world
Work with autonomy and ownership on high-impact projects
Join a collaborative, global team with experience from leading tech and fitness companies
Enjoy competitive salary, equity, and performance bonuses
Build something meaningful that helps people live better, healthier lives
Everfit is an equal opportunity employer committed to building a diverse and inclusive team. We make employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability, or any other protected status.
Ready to dive into data in the fitness intelligence space? We'd love to hear from you.
$124k-169k yearly est. 3d ago
Data/Full Stack Engineer, Data Storage & Ingestion Consultant
Eon Systems PBC
Data engineer job in San Francisco, CA
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
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$110k-157k yearly est. 3d ago
Staff Machine Learning Data Engineer
Backflip 3.7
Data engineer job in San Francisco, CA
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 DataEngineer 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 dataengineering 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.
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$126k-178k yearly est. 2d ago
Senior Data Engineer, Card Data Platform
Capital One 4.7
Data engineer job in San Francisco, CA
A financial services company in San Francisco seeks a Distinguished DataEngineer 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 dataengineering, a Bachelor's degree, and proficiency in modern data practices to drive customer value through analytics and automation.
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$106k-144k yearly est. 4d ago
Foundry Data Engineer: ETL Automation & Dashboards
Data Freelance Hub 4.5
Data engineer job in San Francisco, CA
A data consulting firm based in San Francisco is seeking a Palantir Foundry Consultant for a contract position. The ideal candidate should have strong experience in Palantir Foundry, SQL, and PySpark, with proven skills in data pipeline development and ETL automation. Responsibilities include building data pipelines, implementing interactive dashboards, and leveraging data analysis for actionable insights. This on-site role offers an excellent opportunity for those experienced in the field.
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$114k-160k yearly est. 6d ago
Senior Data Engineer
X4 Engineering
Data engineer job in Sonoma, CA
The Company:
A data services company based in the heart of San Francisco, are looking for a Senior DataEngineer. They are a team of passionate engineers and data experts that are working on a variety of different project, primarily in the financial services sector, helping organizations build scalable, modern data platforms. This is a hands-on, full-time role with close collaboration alongside the CTO and senior engineers, offering strong influence over technical direction and delivery.
The Role:
This is an on-site position in the downtown San Francisco where you will be working as part of a close-knit team, collaborating on projects in their brand new office. You will be working across end-to-end data projects, including:
Building and maintaining data pipelines and ETL processes.
Sourcing and integrating third-party APIs and datasets.
Batch and near-real-time processing (cloud agnostic).
Downstream analytics and reporting using tools like Sigma Computing and Omnium Analytics.
Collaborating with the CTO and engineering team to deliver client solutions.
Key Skills:
5+ years' dataengineering experience
Strong Python, BigQuery, and cloud (GCP or similar)
Solid ETL and pipeline background
Comfortable with large-scale data
Nice to Have
Beam, Dataflow, Spark, or Hadoop
Tableau or Looker
ML/AI exposure
Kafka or Pub/Sub
Given the varied nature of the work, a broad range of technology experience is valued. You don't need to have experience with every tool listed below to be considered, so we encourage you to apply.
This role is 5 days a week on-site in downtown San Francisco. Looking to pay between $170,000-$220,000 with a bonus between 15-20%.
Benefits
Health, Dental & Vision covered
Unlimited PTO
401(k) with employer contribution
Commuter benefits.
$110k-157k yearly est. 3d ago
Multi-Channel Demand Gen Leader - Data SaaS
Motherduck Corporation
Data engineer job in San Francisco, CA
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.
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$112k-157k yearly est. 3d ago
Workday HRIS Lead & Data Insights
Nuvation Bio, Inc. 4.1
Data engineer job in San Francisco, CA
A leading biopharmaceutical company in San Francisco is seeking a Senior Manager, HRIS to manage the Workday implementation and HR data reporting. The ideal candidate will have extensive experience with Workday, project management skills, and a strong technical background. Key responsibilities include leading system implementation, maintaining HR data integrity, and providing insightful HR metrics to aid decision-making. This role also offers competitive compensation and benefits package including unlimited vacation and health coverage.
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$111k-156k yearly est. 4d ago
Data Scientist
Talent Software Services 3.6
Data engineer job in Novato, CA
Are you an experienced Data Scientist with a desire to excel? If so, then Talent Software Services may have the job for you! Our client is seeking an experienced Data Scientist to work at their company in Novato, CA.
Client's Data Science is responsible for designing, capturing, analyzing, and presenting data that can drive key decisions for Clinical Development, Medical Affairs, and other business areas of Client. With a quality-by-design culture, Data Science builds quality data that is fit-for-purpose to support statistically sound investigation of critical scientific questions. The Data Science team develops solid analytics that are visually relevant and impactful in supporting key data-driven decisions across Client. The Data Management Science (DMS) group contributes to Data Science by providing complete, correct, and consistent analyzable data at data, data structure and documentation levels following international standards and GCP. The DMS Center of Risk Based Quality Management (RBQM) sub-function is responsible for the implementation of a comprehensive, cross-functional strategy to proactively manage quality risks for clinical trials. Starting at protocol development, the team collaborates to define critical-to-quality factors, design fit-for-purpose quality strategies, and enable ongoing oversight through centralized monitoring and data-driven risk management. The RBQM Data Scientist supports central monitoring and risk-based quality management (RBQM) for clinical trials. This role focuses on implementing and running pre-defined KRIs, QTLs, and other risk metrics using clinical data, with strong emphasis on SAS programming to deliver robust and scalable analytics across multiple studies.
Primary Responsibilities/Accountabilities:
The RBQM Data Scientist may perform a range of the following responsibilities, depending upon the study's complexity and the study's development stage:
Implement and maintain pre-defined KRIs, QTLs, and triggers using robust SAS programs/macros across multiple clinical studies.
Extract, transform, and integrate data from EDC systems (e.g., RAVE) and other clinical sources into analysis-ready SAS datasets.
Run routine and ad-hoc RBQM/central monitoring outputs (tables, listings, data extracts, dashboard feeds) to support signal detection and study review.
Perform QC and troubleshooting of SAS code; ensure outputs are accurate and efficient.
Maintain clear technical documentation (specifications, validation records, change logs) for all RBQM programs and processes.
Collaborate with Central Monitors, Central Statistical Monitors, Data Management, Biostatistics, and Study Operations to understand requirements and ensure correct implementation of RBQM metrics.
Qualifications:
PhD, MS, or BA/BS in statistics, biostatistics, computer science, data science, life science, or a related field.
Relevant clinical development experience (programming, RBM/RBQM, Data Management), for example:
PhD: 3+ years
MS: 5+ years
BA/BS: 8+ years
Advanced SAS programming skills (hard requirement) in a clinical trials environment (Base SAS, Macro, SAS SQL; experience with large, complex clinical datasets).
Hands-on experience working with clinical trial data.•Proficiency with Microsoft Word, Excel, and PowerPoint.
Technical - Preferred / Strong Plus
Experience with RAVE EDC.
Awareness or working knowledge of CDISC, CDASH, SDTM standards.
Exposure to R, Python, or JavaScript and/or clinical data visualization tools/platforms.
Preferred:
Knowledge of GCP, ICH, FDA guidance related to clinical trials and risk-based monitoring.
Strong analytical and problem-solving skills; ability to interpret complex data and risk outputs.
Effective communication and teamwork skills; comfortable collaborating with cross-functional, global teams.
Ability to manage multiple programming tasks and deliver high-quality work in a fast-paced environment.
$99k-138k yearly est. 2d ago
Lead AI Engineer - Build Autonomous AI Agents & Real-Time Infra
CEF Ai
Data engineer job in San Francisco, CA
A pioneering AI infrastructure company in San Francisco is seeking a Lead AI Engineer to drive the development and implementation of cutting-edge AI solutions. The ideal candidate will have extensive experience in launching tech solutions and a strong understanding of modern AI workflows. As part of a close-knit team led by SV startup veterans, this position offers the chance to make a significant impact in building real-time, privacy-preserving AI systems and to work directly with company leaders.
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$76k-116k yearly est. 4d ago
Security Engineering Lead: Build Secure, Scalable Systems
Airbyte
Data engineer job in San Francisco, CA
A growing tech company in San Francisco is seeking a Security Engineering Lead to own security, compliance, and privacy. The role involves leading security initiatives, setting priorities, and collaborating with cross-functional teams. Candidates should have extensive security experience, including hands-on knowledge of cloud security and compliance frameworks such as SOC 2 and ISO 27001. Strong communication and risk management skills are essential to foster a secure environment as the company scales.
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$76k-116k yearly est. 2d ago
Staff Data Scientist - Sales Analytics
Harnham
Data engineer job in San Francisco, CA
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 looking for a Staff Data Scientist to drive Sales and Go-to-Market (GTM) analytics, applying advanced modeling and experimentation to accelerate revenue growth and optimize the full sales funnel.
About the Role
As the senior data scientist supporting Sales and GTM, you will combine statistical modeling, experimentation, and advanced analytics to inform strategy and guide decision-making across our revenue organization. Your work will help leadership understand pipeline health, predict outcomes, and identify the levers that unlock sustainable growth.
Key Responsibilities
Model the Business: Build forecasting and propensity models for pipeline generation, conversion rates, and revenue projections.
Optimize the Sales Funnel: Analyze lead scoring, opportunity progression, and deal velocity to recommend improvements in acquisition, qualification, and close rates.
Experimentation & Causal Analysis: Design and evaluate experiments (A/B tests, uplift modeling) to measure the impact of pricing, incentives, and campaign initiatives.
Advanced Analytics for GTM: Apply machine learning and statistical techniques to segment accounts, predict churn/expansion, and identify high-value prospects.
Cross-Functional Partnership: Work closely with Sales, Marketing, RevOps, and Product to influence GTM strategy and ensure data-driven decisions.
Data Infrastructure Collaboration: Partner with Analytics Engineering to define data requirements, ensure data quality, and enable self-serve reporting.
Strategic Insights: Present findings to executive leadership, translating complex analyses into actionable recommendations.
About You
Experience: 6+ years in data science or advanced analytics roles, with significant time spent in B2B SaaS or developer tools environments.
Technical Depth: Expert in SQL and proficient in Python or R for statistical modeling, forecasting, and machine learning.
Domain Knowledge: Strong understanding of sales analytics, revenue operations, and product-led growth (PLG) motions.
Analytical Rigor: Skilled in experimentation design, causal inference, and building predictive models that influence GTM strategy.
Communication: Exceptional ability to tell a clear story with data and influence senior stakeholders across technical and business teams.
Business Impact: Proven record of driving measurable improvements in pipeline efficiency, conversion rates, or revenue outcomes.
$200k-250k yearly 1d ago
Data Scientist
Everfit 3.8
Data engineer job in San Francisco, CA
Data Scientist Everfit | Hybrid, San Francisco Bay Area
Everfit is a fitness technology company building an AI-powered coaching platform that serves 280,000+ coaches and Millions of training clients globally. We're transforming how fitness professionals deliver personalized training and nutrition guidance to their clients through intelligent automation and data-driven insights.
About the Role
We're looking for a senior data scientist who is passionate about fitness and energized by turning data into actionable insights that help coaches and their clients succeed. You'll play a critical role in understanding user behavior, product performance, and business metrics to inform strategic decisions as we scale our platform.
What You'll Do
Product Analytics & User Insights
Define and track key product metrics (activation, engagement, retention, churn) to measure product health and success.
Conduct cohort, funnel, and retention analyses to uncover behavioral insights and inform feature prioritization.
Identify opportunities to improve onboarding, engagement, and coach-client interactions.
Experimentation & A/B Testing
Own the experimentation framework and guide teams through hypothesis design, sample sizing, execution, and interpretation.
Strategic Impact & Roadmapping
Collaborate with leadership to translate data insights into roadmap priorities and measurable business outcomes.
Build predictive models and scenario analyses to support forecasting, pricing, and product investment decisions.
Establish best practices in data instrumentation, dashboarding, and self-serve analytics across teams.
Technical Foundations
Partner with dataengineering to improve pipelines and instrumentation.
Leverage tools such as SQL, Python/R, data visualization platforms, and experimentation platforms.
Marketing Analytics & Optimization
Analyze customer acquisition funnels and marketing performance to identify high-impact opportunities for growth and conversion.
Partner with marketing and growth teams to design and evaluate campaign experiments
What We're Looking For
4-6 years of experience in a data analyst or analytics role, preferably at a growth-stage tech company
Strong proficiency in SQL and experience setting up data pipelines, transforming data, and analyzing large datasets
Deep experience with creating dashboards and providing analysis on product analytics and data visualization tools (Amplitude, Looker, Tableau, Mode, or similar)
Understanding of SaaS metrics and cohort analysis
Experience with translating numerical findings into clear insights for non-technical team members
Genuine passion for fitness, health, or wellness (we build for coaches so you need to understand their world)
Bonus Points:
Experience with Python or R for statistical analysis
Experience in a PLG (Product-Led Growth) environment
Experience working at a company during a hypergrowth phase
Background in fitness, health, wellness, or coaching industries
You'll thrive here if you:
Are naturally curious and love asking "why" until you find the answer
Are excited by fast-paced, high-growth environments with a passion for building out systems for scaling
Enjoy collaborating with global teams and making complex topics understandable
Are comfortable with ambiguity and can structure your own work
Care deeply about the impact your insights have on real coaches and their clients
Why Join Everfit
Establish the foundations for Fitness Intelligence and help shape the future of coaching for millions around the world
Work with autonomy and ownership on high-impact projects
Join a collaborative, global team with experience from leading tech and fitness companies
Enjoy competitive salary, equity, and performance bonuses
Build something meaningful that helps people live better, healthier lives
Everfit is an equal opportunity employer committed to building a diverse and inclusive team. We make employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability, or any other protected status.
Ready to dive into data in the fitness intelligence space? We'd love to hear from you.
$123k-169k yearly est. 3d ago
Senior Data Engineer
X4 Engineering
Data engineer job in San Francisco, CA
The Company:
A data services company based in the heart of San Francisco, are looking for a Senior DataEngineer. They are a team of passionate engineers and data experts that are working on a variety of different project, primarily in the financial services sector, helping organizations build scalable, modern data platforms. This is a hands-on, full-time role with close collaboration alongside the CTO and senior engineers, offering strong influence over technical direction and delivery.
The Role:
This is an on-site position in the downtown San Francisco where you will be working as part of a close-knit team, collaborating on projects in their brand new office. You will be working across end-to-end data projects, including:
Building and maintaining data pipelines and ETL processes.
Sourcing and integrating third-party APIs and datasets.
Batch and near-real-time processing (cloud agnostic).
Downstream analytics and reporting using tools like Sigma Computing and Omnium Analytics.
Collaborating with the CTO and engineering team to deliver client solutions.
Key Skills:
5+ years' dataengineering experience
Strong Python, BigQuery, and cloud (GCP or similar)
Solid ETL and pipeline background
Comfortable with large-scale data
Nice to Have
Beam, Dataflow, Spark, or Hadoop
Tableau or Looker
ML/AI exposure
Kafka or Pub/Sub
Given the varied nature of the work, a broad range of technology experience is valued. You don't need to have experience with every tool listed below to be considered, so we encourage you to apply.
This role is 5 days a week on-site in downtown San Francisco. Looking to pay between $170,000-$220,000 with a bonus between 15-20%.
Benefits
Health, Dental & Vision covered
Unlimited PTO
401(k) with employer contribution
Commuter benefits.
The average data engineer in Napa, CA earns between $94,000 and $184,000 annually. This compares to the national average data engineer range of $80,000 to $149,000.
Average data engineer salary in Napa, CA
$131,000
What are the biggest employers of Data Engineers in Napa, CA?
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