Top Data Engineer Jobs in San Francisco Bay Area, CA

The DMS Data Engineer is responsible for analyzing raw data, building data systems and pipelines, conducting complex data analyses, and collaborating on projects to enhance data quality and reliability.

Design, develop and maintain data infrastructure for real-time and batch processing of campaign data, utilizing technologies like Kafka and Spark while ensuring data reliability and performance.

As a Data Engineer, you will build and optimize data pipelines, manage ETL workflows, and ensure efficient data access and quality within the infrastructure.

As a Senior Data Engineer, you will build and optimize foundational datasets, data pipelines, and analytical dashboards while ensuring data quality management.

The Junior Data Engineer will analyze data, build and maintain data pipelines, support CI/CD processes, and assist in IT modernization efforts for a Federal client.

Design and develop Python-based analytics tools for investment research and portfolio analysis, while managing data lakes and AWS solutions.

Lead design and delivery of enterprise data centralization and automation for reporting and BI. Build and maintain ETL/SSIS pipelines, data orchestration, file delivery and quality controls, follow SDLC/agile, mentor junior engineers, and partner with business stakeholders to capture requirements and ensure timely data delivery.

Design, build, and maintain scalable ETL/ELT data pipelines on Databricks and AWS S3; manage large geospatial and temporal datasets; productionize ML models; implement data validation, testing, and monitoring; optimize storage and processing; document workflows; collaborate cross-functionally.

Design, implement, optimize, and maintain scalable, high-availability database solutions for a SaaS healthcare product. Integrate client data, resolve complex data issues, refactor systems for Azure, optimize MSSQL performance, participate in code reviews, and deliver features within Agile/Scrum to ensure reliable, high-performance data services.

The role involves building and optimizing data pipelines, modeling datasets, applying machine learning techniques, and supporting data strategies. Candidates should have experience with Python, data lakes, warehousing, and related technologies.

As a Data Engineer at LiveKit, you will manage the analytics infrastructure, develop scalable GCP-based data pipelines, and ensure effective data movement and transformation processes, while collaborating with the Analytics and engineering teams.

The Data Engineer Senior will optimize data pipelines, work within scrum teams, mentor others, and improve data quality, reliability, and governance.

Design and build Retool's data infrastructure, optimize ETLs, ensure data access and quality, and collaborate with stakeholders across the company.

Design and deploy scalable data infrastructure and models, maintain CDC pipelines, build reporting tools and dashboards, write high-performance SQL, partner with product and engineering to enable enterprise-wide analytics and data-driven decision making.

The Senior Data Engineer will design, implement, and optimize scalable data solutions, working with data pipelines and collaborating with cross-functional teams in healthcare.

Build and maintain cloud data pipelines and ML feature/model workflows in Snowflake and AWS. Implement data ingestion, transformations, quality checks, monitoring, and documentation. Collaborate with data scientists, analysts, and product teams to support analytics, audience insights, rapid prototyping, and reliable production deployments.

Design, build, and maintain ELT pipelines and analytics-ready data models to support reporting, KPIs, and downstream ML use cases; implement data quality, optimize pipeline performance, document lineage, and ensure governance and privacy.

As a Senior Data Engineer, you will guide technical implementations for marketing operations and data science, collaborating with various stakeholders on strategy and infrastructure development.

The Staff Data Engineer will lead financial data operations, ensuring accuracy and reliability of data pipelines, while collaborating with Finance, Product, and Engineering teams to enhance systems and decision-making processes.

Responsible for designing, developing, and maintaining scalable data pipelines and infrastructure, implementing data governance, and collaborating with teams to meet data needs.

The Senior Data Engineer will design and manage data integration, warehousing, and analytics solutions, ensuring data quality and guiding junior engineers while collaborating with technical leaders and external stakeholders.

The Senior Data Engineer will lead BI development, enhance Power BI architecture, mentor developers, and ensure efficient delivery governance for BI projects.

The Senior Data Engineer will build and manage data pipelines in Snowflake, integrate AI systems, and ensure data security and optimization while collaborating across teams to support revenue analytics.

Design and maintain ETL/ELT pipelines for data, optimize workflows for analytics and machine learning, and ensure data quality and governance.

The Senior Data Engineer will design scalable data processing frameworks using Java and Apache Spark, manage data pipelines, and mentor junior engineers.