Top Remote Data Engineer Jobs in San Francisco Bay Area, CA

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 Staff Data Engineer will design and implement a unified semantic data layer, integrating heterogeneous data sources and enabling AI interactions while ensuring security and compliance across the organization.

The Looker Data Engineer will build and optimize data models, develop reporting solutions, and support data-driven decisions using Looker and other technologies.

The Senior Data Engineer will build and maintain data pipelines, optimize data processing, and ensure data privacy and quality within the healthcare tech space.

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.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

The Data Engineer will design and maintain data pipelines, optimize cloud data warehouses, and collaborate with analytics teams while mentoring junior staff.

Design, develop, and manage data infrastructure for internal and client projects, focusing on large-scale data pipelines, APIs, and cloud deployments.

The Data Engineer designs and manages data pipelines for lead generation, collaborates with Sales, analyzes metrics, and ensures data quality and integrity.

Design, build, and maintain scalable data pipelines and tooling to support AI and analytics. Manage datastores (MySQL, Redshift, OpenSearch), implement AWS-based ETL/ELT solutions, collaborate with data science and product teams, and ensure data quality, automation, and production reliability.

As a Senior Data Engineer, you will define and own data pipelines, design schemas, partner with scientists, and improve data infrastructure for Merge Labs' molecular optimization platform.

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

The Principal Data Engineer will design and maintain data systems, evaluate technology solutions, mentor team members, and communicate effectively with stakeholders.

In this role, you'll build and scale high-throughput data pipelines, ensure data quality, and leverage AI for improved data operations. You'll also lead initiatives in a fast-paced environment focused on real estate data engineering.

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 at Common Room, you'll build ETL pipelines, process billions of events daily, and collaborate on backend projects using AWS, Postgres, and Node.js.

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

Build and operate scalable data pipelines and analytics-ready datasets using Python, dbt, and BigQuery. Develop Looker dashboards, ensure data quality and observability, optimize performance and cost, integrate data workflows with backend services and CI/CD, and support analytics, experimentation, and production use cases.

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.

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.

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

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.

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

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.