Top Data Engineer Jobs in San Francisco Bay Area, CA

The Data Engineer Consultant will design and implement scalable data solutions, advise clients on optimizing data environments, and develop ETL pipelines and data models to support business objectives.

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.

As a Data Engineer, you will build and maintain data pipelines, ensure data quality, support ML workflows, and optimize query performance using various technologies.

As a Databricks Data Engineer, you will design, implement, and optimize Databricks solutions, lead projects, gather requirements, and collaborate closely with clients to ensure successful project delivery.

Develop and maintain data infrastructure for safety data analysis, build scalable data pipelines, conduct exploratory analyses, and support regulatory reporting in AV safety.

The Data Migration Engineer migrates customer data into SaaS products, ensuring data quality and business continuity while collaborating with teams and managing customer requirements.

The Data Engineer will build automated pipelines, harmonize messy data, and integrate data operations with an AI mindset. Responsibilities include developing robust workflows, optimizing data processing, collaborating with teams, and maintaining operational excellence.

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 Data Engineer, you'll build data infrastructure for analytics, drive business growth strategies, and enhance personalized user experiences at Eight Sleep.

The role involves designing and maintaining ETL/ELT pipelines, integrating diverse data sources, automating Fabric environments, and collaborating with global teams on data solutions.

The Founding Data Engineer will manage the company's data models, ensure metric integrity, and work with various teams to deliver reliable metrics and reporting systems.

As an AI Data Engineer, you will develop end-to-end data pipelines in Snowflake, enhance AI capabilities, and optimize data quality and infrastructure in collaboration with ML engineers and data scientists.

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.

As an Analytics Engineer, you'll manage the data stack, design database architecture, build data pipelines, and oversee reporting and data quality.

As a Senior Data Engineer, you will design and maintain scalable data models, build production data pipelines, and support analytics across various business functions.

The Data Engineer role involves designing and maintaining AWS-cloud-native data systems, developing ETL processes, optimizing data pipelines, and ensuring data security and governance in healthcare data applications.

In this role, you will build and scale data pipelines, develop ETL workflows, ensure data quality, and support AI-driven applications by preparing datasets.

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.

The Principal Data Engineer will lead the design of data frameworks, mentor teams, implement MDM solutions, and ensure data quality across environments.

The Data Engineer will develop and maintain automated data pipelines, enhance data quality and interoperability, and support reporting capabilities for the Department of Veterans Affairs.

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

As a Data Analytics Engineer, you'll build and manage data models in Snowflake, structure datasets for optimal AI performance, and own data transformation while ensuring quality and accessibility for all teams.

The Data Engineer is responsible for building and maintaining ETL/ELT pipelines, optimizing data storage formats, managing CI/CD pipelines, and creating visualizations with actionable insights, focusing on reliability and data quality.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.