Data scientist jobs in Erie, PA

Job Family: Data Science Consulting Travel Required: Up to 10% Clearance Required: Ability to Obtain Public Trust About our AI and Data Capability Team Our consultants on the AI and Data Analytics Capability team help clients maximize the value of their data and automate business processes. This high performing team works with clients to implement the full spectrum of data analytics and data science services, from data architecture and storage to data engineering and querying, to data visualization and dashboarding, to predictive analytics, machine learning, and artificial intelligence as well as intelligent automation. Our services enable our clients to define their information strategy, enable mission critical insights and data-driven decision making, reduce cost and complexity, increase trust, and improve operational effectiveness. What You Will Do: Data Collection & Management: Identify, gather, and manage data from primary and secondary sources, ensuring its accuracy and integrity. Data Cleaning & Preprocessing: Clean raw data by identifying and addressing inconsistencies, missing values, and errors to prepare it for analysis. Data Analysis & Interpretation: Apply statistical techniques and analytical methods to explore datasets, discover trends, find patterns, and derive insights. Data Visualization & Reporting: Develop reports, dashboards, and visualizations using tools like Tableau or Power BI to present complex findings clearly to stakeholders. Collaboration & Communication: Work with cross-functional teams, understand business requirements, and effectively communicate insights to support data-driven decision-making. Problem Solving: Address specific business challenges by using data to identify underperforming processes, pinpoint areas for growth, and determine optimal strategies. What You Will Need: US Citizenship is required Bachelor's degree is required Minimum THREE (3) Years Experience using Power BI, Tableau and other visualization tools to develop intuitive and user friendly dashboards and visualizations. Skilled in SQL, R, and other languages to assist in database querying and statistical programming. Strong foundational knowledge and experience in statistics, probability, and experimental design. Familiarity with cloud platforms (e.g., Amazon Web Services, Azure, or Google Cloud) and containerization (e.g., Docker). Experience applying data governance concepts and techniques to assure greater data quality and reliability. he curiosity and creativity to uncover hidden patterns and opportunities. Strong communication skills to bridge technical and business worlds. What Would Be Nice To Have: Hands-on experience with Python, SQL, and modern ML frameworks. Experience in data and AI system development, with a proven ability to design scalable architectures and implement reliable models. Expertise in Python or Java for data processing. Demonstrated work experience within the public sector. Ability to support business development including RFP/RFQ/RFI responses involving data science / analytics. The annual salary range for this position is $113,000.00-$188,000.00. Compensation decisions depend on a wide range of factors, including but not limited to skill sets, experience and training, security clearances, licensure and certifications, and other business and organizational needs. What We Offer: Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace. Benefits include: Medical, Rx, Dental & Vision Insurance Personal and Family Sick Time & Company Paid Holidays Position may be eligible for a discretionary variable incentive bonus Parental Leave and Adoption Assistance 401(k) Retirement Plan Basic Life & Supplemental Life Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts Short-Term & Long-Term Disability Student Loan PayDown Tuition Reimbursement, Personal Development & Learning Opportunities Skills Development & Certifications Employee Referral Program Corporate Sponsored Events & Community Outreach Emergency Back-Up Childcare Program Mobility Stipend About Guidehouse Guidehouse is an Equal Opportunity Employer-Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation. Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco. If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at ************** or via email at RecruitingAccommodation@guidehouse.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation. All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains including @guidehouse.com or ************************. Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse. Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process. If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse's Ethics Hotline. If you want to check the validity of correspondence you have received, please contact *************************. Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant's dealings with unauthorized third parties. Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.

Candidates MUST go on-site at one of the following locations Columbus, OH Cincinnati, OH Cleveland, OH Indianapolis, IN Hagerstown, MD Chicago, IL Detroit, MI Minnetonka, MN Houston, TX Charlotte, NC Akron, OH Experience: · Master's degree and 5+ years of experience related work experience using statistics and machine learning to solve complex business problems, experience conducting statistical analysis with advanced statistical software, scripting languages, and packages, experience with big data analysis tools and techniques, and experience building and deploying predictive models, web scraping, and scalable data pipelines · Expert understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling Python, R, or SAS SQL and some sort of lending experience (i.e. HELOC, Mortgage etc) is most important Excellent communication skills If a candidate has cred card experience (i.e. Discover or Bread financial ) THEY ARE A+ fit! Education: Master's degree or PhD in computer science, statistics, economics or related fields Responsibilities: · Prioritizes analytical projects based on business value and technological readiness Performs large-scale experimentation and build data-driven models to answer business questions Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence Evangelizes best practices to analytics and products teams Acts as the go-to resource for machine learning across a range of business needs Owns the entire model development process, from identifying the business requirements, data sourcing, model fitting, presenting results, and production scoring Provides leadership, coaching, and mentoring to team members and develops the team to work with all areas of the organization Works with stakeholders to ensure that business needs are clearly understood and that services meet those needs Anticipates and analyzes trends in technology while assessing the emerging technology's impact(s) Coaches' individuals through change and serves as a role model Skills: · Up-to-date knowledge of machine learning and data analytics tools and techniques Strong knowledge in predictive modeling methodology Experienced at leveraging both structured and unstructured data sources Willingness and ability to learn new technologies on the job Demonstrated ability to communicate complex results to technical and non-technical audiences Strategic, intellectually curious thinker with focus on outcomes Professional image with the ability to form relationships across functions Ability to train more junior analysts regarding day-to-day activities, as necessary Proven ability to lead cross-functional teams Strong experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker) Strong experience with machine learning environments (e.g., TensorFlow, scikit-learn, caret) Demonstrated Expertise with at least one Data Science environment (R/RStudio, Python, SAS) and at least one database architecture (SQL, NoSQL) Financial Services background preferred

THIS IS A W2 (NOT C2C OR REFERRAL BASED) CONTRACT OPPORTUNITY REMOTE MOSTLY WITH 1 DAY/MO ONSITE IN CINCINNATI-LOCAL CANDIDATES TAKE PREFERENCE RATE: $75-85/HR WITH BENEFITS We are seeking a highly skilled Data Architect to function in a consulting capacity to analyze, redesign, and optimize a Medical Payments client's environment. The ideal candidate will have deep expertise in SQL, Azure cloud services, and modern data architecture principles. Responsibilities Design and maintain scalable, secure, and high-performing data architectures. Lead migration and modernization projects in heavy use production systems. Develop and optimize data models, schemas, and integration strategies. Implement data governance, security, and compliance standards. Collaborate with business stakeholders to translate requirements into technical solutions. Ensure data quality, consistency, and accessibility across systems. Required Qualifications Bachelor's degree in Computer Science, Information Systems, or related field. Proven experience as a Data Architect or similar role. Strong proficiency in SQL (query optimization, stored procedures, indexing). Hands-on experience with Azure cloud services for data management and analytics. Knowledge of data modeling, ETL processes, and data warehousing concepts. Familiarity with security best practices and compliance frameworks. Preferred Skills Understanding of Electronic Health Records systems. Understanding of Big Data technologies and modern data platforms outside the scope of this project.

Godel Terminal is a cutting edge financial platform that puts the world's financial data at your fingertips. From Equities and SEC filings, to global news delivered in milliseconds, thousands of customers rely on Godel every day to be their guide to the world of finance. We are looking for a senior engineer in New York City to join our team and help build out live data services as well as historical data for US markets and international exchanges. This position will specifically work on new asset classes and exchanges, but will be expected to contribute to the core architecture as we expand to international markets. Our team works quickly and efficiently, we are opinionated but flexible when it's time to ship. We know what needs to be done, and how to do it. We are laser focused on not just giving our customers what they want, but exceeding their expectations. We are very proud that when someone opens the app the first time they ask: “How on earth does this work so fast”. If that sounds like a team you want to be part of, here is what we need from you: Minimum qualifications: Able to work out of our Manhattan office minimum 4 days a week 5+ years of experience in a financial or startup environment 5+ years of experience working on live data as well as historical data 3+ years of experience in Java, Python, and SQL Experience managing multiple production ETL pipelines that reliably store and validate financial data Experience launching, scaling, and improving backend services in cloud environments Experience migrating critical data across different databases Experience owning and improving critical data infrastructure Experience teaching best practices to junior developers Preferred qualifications: 5+ years of experience in a fintech startup 5+ years of experience in Java, Kafka, Python, PostgreSQL 5+ years of experience working with Websockets like RXStomp or Socket.io 5+ years of experience wrangling cloud providers like AWS, Azure, GCP, or Linode 2+ years of experience shipping and optimizing Rust applications Demonstrated experience keeping critical systems online Demonstrated creativity and resourcefulness under pressure Experience with corporate debt / bonds and commodities data Salary range begins at $150,000 and increases with experience Benefits: Health Insurance, Vision, Dental To try the product, go to *************************

Hi, I hope you are doing well! We have an opportunity for Azure Data Architect with one of our clients for Malvern PA. Please see the job details below and let me know if you would be interested in this role. If interested, please send me a copy of your resume, contact details, availability, and a good time to connect with you. Title: Azure Data Architect Location: Malvern PA Terms: Long Term Contract JOB DESCRIPTION: Required Skills and Experience Technical Expertise Strong proficiency in Azure services: Data Factory, Synapse, Databricks, Data Lake, Power BI. Experience with data modeling, ETL design, and data warehousing. Knowledge of SQL, NoSQL, PySpark, and BI tools. Architecture and Strategy 7+ years in data architecture roles; 3+ years with Azure data solutions. Familiarity with Lakehouse architecture, Delta/Parquet formats, and data governance tools. Soft Skills Excellent communication and stakeholder management. Ability to lead cross-functional teams and influence technical decisions. Preferred Experience in regulated industries (e.g., Financial Services). Knowledge of Microsoft Fabric, Generative AI, and RAG-based architectures. Education Bachelor's or Master's degree in Computer Science, Information Systems, or related fields. Certifications like Microsoft Certified: Azure Solutions Architect Expert or Azure Data Engineer Associate are highly desirable. Thank you! Amit Jha Senior Recruiter | BeaconFire Inc. 📧 ***********************

DL Software produces Godel, a financial information and trading terminal. Role Description This is a full-time, on-site role based in New York, NY, for a Data Engineer. The Data Engineer will design, build, and maintain scalable data systems and pipelines. Responsibilities include data modeling, developing and managing ETL workflows, optimizing data storage solutions, and supporting data warehousing initiatives. The role also involves collaborating with cross-functional teams to improve data accessibility and analytics capabilities. Qualifications Strong proficiency in Data Engineering and Data Modeling Mandatory: strong experience in global financial instruments including equities, fixed income, options and exotic asset classes Strong Python background Expertise in Extract, Transform, Load (ETL) processes and tools Experience in designing, managing, and optimizing Data Warehousing solutions

We are seeking a highly skilled Analytics Data Engineer with deep expertise in building scalable data solutions on the AWS platform. The ideal candidate is a 10/10 expert in Python and PySpark, with strong working knowledge of SQL. This engineer will play a critical role in translating business and end-user needs into robust analytics products-spanning ingestion, transformation, curation, and enablement for downstream reporting and visualization. You will work closely with both business stakeholders and IT teams to design, develop, and deploy advanced data pipelines and analytical capabilities that power enterprise decision-making. Key Responsibilities Data Engineering & Pipeline Development Design, develop, and optimize scalable data ingestion pipelines using Python, PySpark, and AWS native services. Build end-to-end solutions to move large-scale big data from source systems into AWS environments (e.g., S3, Redshift, DynamoDB, RDS). Develop and maintain robust data transformation and curation processes to support analytics, dashboards, and business intelligence tools. Implement best practices for data quality, validation, auditing, and error-handling within pipelines. Analytics Solution Design Collaborate with business users to understand analytical needs and translate them into technical specifications, data models, and solution architectures. Build curated datasets optimized for reporting, visualization, machine learning, and self-service analytics. Contribute to solution design for analytics products leveraging AWS services such as AWS Glue, Lambda, EMR, Athena, Step Functions, Redshift, Kinesis, Lake Formation, etc. Cross-Functional Collaboration Work with IT and business partners to define requirements, architecture, and KPIs for analytical solutions. Participate in Daily Scrum meetings, code reviews, and architecture discussions to ensure alignment with enterprise data strategy and coding standards. Provide mentorship and guidance to junior engineers and analysts as needed. Engineering (Supporting Skills) Employ strong skills in Python, Pyspark and SQL to support data engineering tasks, broader system integration requirements, and application layer needs. Implement scripts, utilities, and micro-services as needed to support analytics workloads. Required Qualifications 5+ years of professional experience in data engineering, analytics engineering, or full-stack data development roles. Expert-level proficiency (10/10) in: Python PySpark Strong working knowledge of: SQL and other programming languages Demonstrated experience designing and delivering big-data ingestion and transformation solutions through AWS. Hands-on experience with AWS services such as Glue, EMR, Lambda, Redshift, S3, Kinesis, CloudFormation, IAM, etc. Strong understanding of data warehousing, ETL/ELT, distributed computing, and data modeling. Ability to partner effectively with business stakeholders and translate requirements into technical solutions. Strong problem-solving skills and the ability to work independently in a fast-paced environment. Preferred Qualifications Experience with BI/Visualization tools such as Tableau Experience building CI/CD pipelines for data products (e.g., Jenkins, GitHub Actions). Familiarity with machine learning workflows or MLOps frameworks. Knowledge of metadata management, data governance, and data lineage tools.

Immediate need for a talented Senior Data Engineer. This is a 06+ months contract opportunity with long-term potential and is located in Columbus, OH(Remote). Please review the job description below and contact me ASAP if you are interested. Job ID: 25-95277 Pay Range: $70 - $71 /hour. Employee benefits include, but are not limited to, health insurance (medical, dental, vision), 401(k) plan, and paid sick leave (depending on work location). Key Responsibilities: Working with Marketing data partners and build data pipelines to automate the data feeds from the partners to internal systems on Snowflake. Working with Data Analysts to understand their data needs and prepare the datasets for analytics. Work with Data Scientists to build the infrastructure to deploy the models, monitor the performance, and build the necessary audit infrastructure. Key Requirements and Technology Experience: Key skills; Snowflake, Python and AWS Experience with building data pipelines, data pipeline infrastructure and related tools and environments used in analytics and data science (ex: Python, Unix) Experience in developing analytic workloads with AWS Services, S3, Simple Queue Service (SQS), Simple Notification Service (SNS), Lambda, EC2, ECR and Secrets Manager. Strong proficiency in Python, SQL, Linux/Unix shell scripting, GitHub Actions or Docker, Terraform or CloudFormation, and Snowflake. Order of Importance: Terraform, Docker, GitHub Actions OR Jenkins Experience with orchestration tools such as Prefect, DBT, or Airflow. Experience automating data ingestion, processing, and reporting/monitoring. Experience with other relevant tools used in data engineering (e.g., SQL, GIT, etc.) Ability to set up environments (Dev, QA, and Prod) using GitHub repo and GitHub rules/methodologies; how to maintain (via SQL coding and proper versioning) Our client is a leading Insurance Industry, and we are currently interviewing to fill this and other similar contract positions. If you are interested in this position, please apply online for immediate consideration Pyramid Consulting, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, colour, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. By applying to our jobs, you agree to receive calls, AI-generated calls, text messages, or emails from Pyramid Consulting, Inc. and its affiliates, and contracted partners. Frequency varies for text messages. Message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You can reply STOP to cancel and HELP for help. You can access our privacy policy here.

We're seeking a skilled Data Engineer based in Columbus, OH, to support a high-impact data initiative. The ideal candidate will have hands-on experience with Python, Databricks, SQL, and version control systems, and be comfortable building and maintaining robust, scalable data solutions. Key Responsibilities Design, implement, and optimize data pipelines and workflows within Databricks. Develop and maintain data models and SQL queries for efficient ETL processes. Partner with cross-functional teams to define data requirements and deliver business-ready solutions. Use version control systems to manage code and ensure collaborative development practices. Validate and maintain data quality, accuracy, and integrity through testing and monitoring. Required Skills Proficiency in Python for data engineering and automation. Strong, practical experience with Databricks and distributed data processing. Advanced SQL skills for data manipulation and analysis. Experience with Git or similar version control tools. Strong analytical mindset and attention to detail. Preferred Qualifications Experience with cloud platforms (AWS, Azure, or GCP). Familiarity with enterprise data lake architectures and best practices. Excellent communication skills and the ability to work independently or in team environments.

As an IoT Data Engineer at CurvePoint, you will design, build, and optimize the data pipelines that power our Wi-AI sensing platform. Your work will focus on reliable, low-latency data acquisition from constrained on-prem IoT devices, efficient buffering and streaming, and scalable cloud-based storage and training workflows. You will own how raw sensor data (e.g., wireless CSI, video, metadata) moves from edge devices with limited disk and compute into durable, well-structured datasets used for model training, evaluation, and auditability. You will work closely with hardware, ML, and infrastructure teams to ensure our data systems are fast, resilient, and cost-efficient at scale. Duties and Responsibilities Edge & On-Prem Data Acquisition Design and improve data capture pipelines on constrained IoT devices and host servers (limited disk, intermittent connectivity, real-time constraints). Implement buffering, compression, batching, and backpressure strategies to prevent data loss. Optimize data transfer from edge → on-prem host → cloud. Streaming & Ingestion Pipelines Build and maintain streaming or near-real-time ingestion pipelines for sensor data (e.g., CSI, video, logs, metadata). Ensure data integrity, ordering, and recoverability across failures. Design mechanisms for replay, partial re-ingestion, and audit trails. Cloud Data Pipelines & Storage Own cloud-side ingestion, storage layout, and lifecycle policies for large time-series datasets. Balance cost, durability, and performance across hot, warm, and cold storage tiers. Implement data versioning and dataset lineage to support model training and reproducibility. Training Data Enablement Structure datasets to support efficient downstream ML training, evaluation, and experimentation. Work closely with ML engineers to align data formats, schemas, and sampling strategies with training needs. Build tooling for dataset slicing, filtering, and validation. Reliability & Observability Add monitoring, metrics, and alerts around data freshness, drop rates, and pipeline health. Debug pipeline failures across edge, on-prem, and cloud environments. Continuously improve system robustness under real-world operating conditions. Cross-Functional Collaboration Partner with hardware engineers to understand sensor behavior and constraints. Collaborate with ML engineers to adapt pipelines as model and data requirements evolve. Contribute to architectural decisions as the platform scales from pilots to production deployments. Must Haves Bachelor's degree in Computer Science, Electrical Engineering, or a related field (or equivalent experience). 3+ years of experience as a Data Engineer or Backend Engineer working with production data pipelines. Strong Python skills; experience building reliable data processing systems. Hands-on experience with streaming or near-real-time data ingestion (e.g., Kafka, Kinesis, MQTT, custom TCP/UDP pipelines). Experience working with on-prem systems or edge/IoT devices, including disk, bandwidth, or compute constraints. Familiarity with cloud storage and data lifecycle management (e.g., S3-like object stores). Strong debugging skills across distributed systems. Nice to Have Experience with IoT or sensor data (RF/CSI, video, audio, industrial telemetry). Familiarity with data compression, time-series formats, or binary data handling. Experience supporting ML training pipelines or large-scale dataset management. Exposure to containerized or GPU-enabled data processing environments. Knowledge of data governance, retention, or compliance requirements. Location Pittsburgh, PA (hybrid preferred; some on-site work with hardware teams) Salary $110,000 - $135,000 / year (depending on experience and depth in streaming + IoT systems)

🚀 Market Data Engineer - New York | Cutting-Edge Trading Environment I'm partnered with a leading technology-driven trading team in New York looking to bring on a Market Data Engineer to support global research, trading, and infrastructure groups. This role is central to managing the capture, normalization, and distribution of massive volumes of historical market data from exchanges worldwide. What You'll Do Own large-scale, time-sensitive market data capture + normalization pipelines Improve internal data formats and downstream datasets used by research and quantitative teams Partner closely with infrastructure to ensure reliability of packet-capture systems Build robust validation, QA, and monitoring frameworks for new market data sources Provide production support, troubleshoot issues, and drive quick, effective resolutions What You Bring Experience building or maintaining large-scale ETL pipelines Strong proficiency in Python + Bash, with familiarity in C++ Solid understanding of networking fundamentals Experience with workflow/orchestration tools (Airflow, Luigi, Dagster) Exposure to distributed computing frameworks (Slurm, Celery, HTCondor, etc.) Bonus Skills Experience working with binary market data protocols (ITCH, MDP3, etc.) Understanding of high-performance filesystems and columnar storage formats

Are you a data engineer who loves building systems that power real impact in the world? A fast growing healthcare technology organization is expanding its innovation team and is looking for a Data Engineer II to help build the next generation of its data platform. This team sits at the center of a major transformation effort, partnering closely with engineering, analytics, and product to design the foundation that supports advanced automation, AI, intelligent workflows, and high scale data operations that drive measurable outcomes for hospitals, health systems, and medical groups. In this role, you will design, develop, and maintain software applications that process large volumes of data every day. You will collaborate with cross functional teams to understand data requirements, build and optimize data models, and create systems that ensure accuracy, reliability, and performance. You will write code that extracts, transforms, and loads data from a variety of sources into modern data warehouses and data lakes, while implementing best in class data quality and governance practices. You will work hands on with big data technologies such as Hadoop, Spark, and Kafka, and you will play a critical role in troubleshooting, performance tuning, and ensuring the scalability of complex data applications. To thrive here, you should bring strong problem solving ability, analytical thinking, and excellent communication skills. This is an opportunity to join an expanding innovation group within a leading healthcare platform that is investing heavily in data, AI, and the future of intelligent revenue operations. If you want to build systems that make a real difference and work with teams that care deeply about improving patient experiences and provider performance, this is a chance to do highly meaningful engineering at scale.

Hey All, We are looking for a mid-level data engineer. No third parties As a result of this expansion, we are seeking experienced software Data engineers with 5+ years of relevant experience to support the design and development of a strategic data platform for SMBC Capital Markets and Nikko Securities Group. Qualifications and Skills • Proven experience as a Data Engineer with experience in Azure cloud. • Experience implementing solutions using - • Azure cloud services • Azure Data Factory • Azure Lake Gen 2 • Azure Databases • Azure Data Fabric • API Gateway management • Azure Functions • Well versed with Azure Databricks • Strong SQL skills with RDMS or no SQL databases • Experience with developing APIs using FastAPI or similar frameworks in Python • Familiarity with the DevOps lifecycle (git, Jenkins, etc.), CI/CD processes • Good understanding of ETL/ELT processes • Experience in financial services industry, financial instruments, asset classes and market data are a plus.

The Data Engineer is a technical leader and hands-on developer responsible for designing, building, and optimizing data pipelines and infrastructure to support analytics and reporting. This role will serve as the lead developer on strategic data initiatives, ensuring scalable, high-performance solutions are delivered effectively and efficiently. The ideal candidate is self-directed, thrives in a fast-paced project environment, and is comfortable making technical decisions and architectural recommendations. The ideal candidate has prior experience in modern data platforms, most notable Databricks and the “lakehouse” architecture. They will work closely with cross-functional teams, including business stakeholders, data analysts, and engineering teams, to develop data solutions that align with enterprise strategies and business goals. Experience in the financial industry is a plus, particularly in designing secure and compliant data solutions. Responsibilities: Design, build, and maintain scalable ETL/ELT pipelines for structured and unstructured data. Optimize data storage, retrieval, and processing for performance, security, and cost-efficiency. Ensure data integrity and governance by implementing robust validation, monitoring, and compliance processes. Consume and analyze data from the data pipeline to infer, predict and recommend actionable insight, which will inform operational and strategic decision making to produce better results. Empower departments and internal consumers with metrics and business intelligence to operate and direct our business, better serving our end customers. Determine technical and behavioral requirements, identify strategies as solutions, and section solutions based on resource constraints. Work with the business, process owners, and IT team members to design solutions for data and advanced analytics solutions. Perform data modeling and prepare data in databases for analysis and reporting through various analytics tools. Play a technical specialist role in championing data as a corporate asset. Provide technical expertise in collaborating with project and other IT teams, internal and external to the company. Contribute to and maintain system data standards. Research and recommend innovative, and where possible automated approaches for system data administration tasks. Identify approaches that leverage our resources and provide economies of scale. Engineer system that balances and meets performance, scalability, recoverability (including backup design), maintainability, security, high availability requirements and objectives. Skills: Databricks and related - SQL, Python, PySpark, Delta Live Tables, Data pipelines, AWS S3 object storage, Parquet/Columnar file formats, AWS Glue. Systems Analysis - The application of systems analysis techniques and procedures, including consulting with users, to determine hardware, software, platform, or system functional specifications. Time Management - Managing one's own time and the time of others. Active Listening - Giving full attention to what other people are saying, taking time to understand the points being made, asking questions as appropriate, and not interrupting at inappropriate times. Critical Thinking - Using logic and reasoning to identify the strengths and weaknesses of alternative solutions, conclusions or approaches to problems. Active Learning - Understanding the implications of new information for both current and future problem-solving and decision-making. Writing - Communicating effectively in writing as appropriate for the needs of the audience. Speaking - Talking to others to convey information effectively. Instructing - Teaching others how to do something. Service Orientation - Actively looking for ways to help people. Complex Problem Solving - Identifying complex problems and reviewing related information to develop and evaluate options and implement solutions. Troubleshooting - Determining causes of operating errors and deciding what to do about it. Judgment and Decision Making - Considering the relative costs and benefits of potential actions to choose the most appropriate one. Experience and Education: High School Diploma (or GED or High School Equivalence Certificate). Associate degree or equivalent training and certification. 5+ years of experience in data engineering including SQL, data warehousing, cloud-based data platforms. Databricks experience. 2+ years Project Lead or Supervisory experience preferred. Must be legally authorized to work in the United States. We are unable to sponsor or take over sponsorship at this time.

Title: Data Engineer (Web Scraping technologies) Duration: FTE/Perm Salary: 125-190k plus bonus Responsibilities: Utilize AI Models, Code, Libraries or applications to enable a scalable Web Scraping capability Web Scraping Request Management including intake, assessment, accessing sites to scrape, utilizing tools to scrape, storage of scrape, validation and entitlement to users Fielding Questions from users about the scrapes and websites Coordinating with Compliance on approvals and TOU reviews Some Experience building Data pipelines in AWS platform utilizing existing tools like Cron, Glue, Eventbridge, Python based ETL, AWS Redshift Normalizing/standardizing vendor data, firm data for firm consumption Implement data quality checks to ensure reliability and accuracy of scraped data Coordinate with Internal teams on delivery, access, requests, support Promote Data Engineering best practices Required Skills and Qualifications: Bachelor's degree in computer science, Engineering, Mathematics or related field 2-5 experience in a similar role Prior buy side experience is strongly preferred (Multi-Strat/Hedge Funds) Capital markets experience is necessary with good working knowledge of reference data across asset classes and experience with trading systems AWS cloud experience with commons services (S3, lambda, cron, Event Bridge etc.) Experience with web-scraping frameworks (Scrapy, BeautifulSoup, Selenium, Playwright etc.) Strong hands-on skills with NoSQL and SQL databases, programming in Python, data pipeline orchestration tools and analytics tools Familiarity with time series data and common market data sources (Bloomberg, Refinitiv etc.) Familiarity with modern Dev Ops practices and infrastructure-as-code tools (e.g. Terraform, CloudFormation) Strong communication skills to work with stakeholders across technology, investment, and operations teams.

The team is seeking a Data Engineer experienced in implementing modern data solutions in Azure, with strong hands-on skills in Databricks, Spark, Python, and cloud-based DataOps practices. The Data Engineer will analyze, design, and develop data products, pipelines, and information architecture deliverables, focusing on data as an enterprise asset. This role also supports cloud infrastructure automation and CI/CD using Terraform, GitHub, and GitHub Actions to deliver scalable, reliable, and secure data solutions. Requirements: • 5+ years of experience as a Data Engineer • Hands-on experience with Azure Databricks, Spark, and Python • Experience with Delta Live Tables (DLT) or Databricks SQL • Strong SQL and database background • Experience with Azure Functions, messaging services, or orchestration tools • Familiarity with data governance, lineage, or cataloging tools (e.g., Purview, Unity Catalog) • Experience monitoring and optimizing Databricks clusters or workflows • Experience working with Azure cloud data services and understanding how they integrate with Databricks and enterprise data platforms • Experience with Terraform for cloud infrastructure provisioning • Experience with GitHub and GitHub Actions for version control and CI/CD automation • Strong understanding of distributed computing concepts (partitions, joins, shuffles, cluster behavior) • Familiarity with SDLC and modern engineering practices • Ability to balance multiple priorities, work independently, and stay organized Key Responsibilities • Analyze, design, and develop enterprise data solutions with a focus on Azure, Databricks, Spark, Python, and SQL • Develop, optimize, and maintain Spark/PySpark data pipelines, including managing performance issues such as data skew, partitioning, caching, and shuffle optimization • Build and support Delta Lake tables and data models for analytical and operational use cases • Apply reusable design patterns, data standards, and architecture guidelines across the enterprise, including collaboration with when needed • Use Terraform to provision and manage cloud and Databricks resources, supporting Infrastructure as Code (IaC) practices • Implement and maintain CI/CD workflows using GitHub and GitHub Actions for source control, testing, and pipeline deployment • Manage Git-based workflows for Databricks notebooks, jobs, and data engineering artifacts • Troubleshoot failures and improve reliability across Databricks jobs, clusters, and data pipelines • Apply cloud computing skills to deploy fixes, upgrades, and enhancements in Azure environments • Work closely with engineering teams to enhance tools, systems, development processes, and data security • Participate in the development and communication of data strategy, standards, and roadmaps • Draft architectural diagrams, interface specifications, and other design documents • Promote the reuse of data assets and contribute to enterprise data catalog practices • Deliver timely and effective support and communication to stakeholders and end users • Mentor team members on data engineering principles, best practices, and emerging technologies

Data Engineer - Job Opportunity Full time Permanent Remote - East coast only Please note this role is open for US citizens or Green Card Holders only We're looking for a Data Engineer to help build and enhance scalable data systems that power analytics, reporting, and business decision-making. This role is ideal for someone who enjoys solving complex technical challenges, optimizing data workflows, and collaborating across teams to deliver reliable, high-quality data solutions. What You'll Do Develop and maintain scalable data infrastructure, cloud-native workflows, and ETL/ELT pipelines supporting analytics and operational workloads. Transform, model, and organize data from multiple sources to enable accurate reporting and data-driven insights. Improve data quality and system performance by identifying issues, optimizing architecture, and enhancing reliability and scalability. Monitor pipelines, troubleshoot discrepancies, and resolve data or platform issues-including participating in on-call support when needed. Prototype analytical tools, automation solutions, and algorithms to support complex analysis and drive operational efficiency. Collaborate closely with BI, Finance, and cross-functional teams to deliver robust and scalable data products. Create and maintain clear, detailed documentation (configurations, specifications, test scripts, and project tracking). Contribute to Agile development processes, engineering excellence, and continuous improvement initiatives. What You Bring Bachelor's degree in Computer Science or a related technical field. 2-4 years of hands-on SQL experience (Oracle, PostgreSQL, etc.). 2-4 years of experience with Java or Groovy. 2+ years working with orchestration and ingestion tools (e.g., Airflow, Airbyte). 2+ years integrating with APIs (SOAP, REST). Experience with cloud data warehouses and modern ELT/ETL frameworks (e.g., Snowflake, Redshift, DBT) is a plus. Comfortable working in an Agile environment. Practical knowledge of version control and CI/CD workflows. Experience with automation, including unit and integration testing. Understanding of cloud storage solutions (e.g., S3, Blob Storage, Object Store). Proactive mindset with strong analytical, logical-thinking, and consultative skills. Ability to reason about design decisions and understand their broader technical impact. Strong collaboration, adaptability, and prioritization abilities. Excellent problem-solving and troubleshooting skills.

1. Comfortable writing and tuning SQL queries on Vertica . 2. Can work with large datasets. 3. Good understanding of MicroStrategy basics like Attributes, Facts, and Hierarchies. 4. Skilled at translating complex technical outputs into simple, meaningful visuals and summaries. 5. Experience optimizing MicroStrategy reports for performance and scalability. 6. Experience creating data pipeline using cloud platforms (edited)

Data Engineer III About the Role We're looking for a Data Engineer III to play a key role in a large-scale data migration initiative within Client's commercial lending, underwriting, and reporting areas. This is a hands-on engineering role that blends technical depth with business analysis, focused on transforming legacy data systems into modern, scalable pipelines. What You'll Do Analyze legacy SQL, DataStage, and SAS code to extract business logic and identify key data dependencies. Document current data usage and evaluate the downstream impact of migrations. Design, build, and maintain data pipelines and management systems to support modernization goals. Collaborate with business and technology teams to translate requirements into technical solutions. Improve data quality, reliability, and performance across multiple environments. Develop backend solutions using Python, Java, or J2EE, and integrate with tools like DataStage and dbt. What You Bring 5+ years of experience with relational and non-relational databases (SQL, Snowflake, DB2, MongoDB). Strong background in legacy system analysis (SQL, DataStage, SAS). Experience with Python or Java for backend development. Proven ability to build and maintain ETL pipelines and automate data processes. Exposure to AWS, Azure, or GCP. Excellent communication and stakeholder engagement skills. Financial domain experience-especially commercial lending or regulatory reporting-is a big plus. Familiarity with Agile methodologies preferred.