Top Data Engineering Jobs in San Francisco, CA

Leads and develops a data engineering team supporting People Analytics. Designs scalable data models, pipelines, semantic layers, testing frameworks, and governance practices. Remains hands-on with production code, reviews, and technical problem-solving. Owns engineering standards across Python, SQL, dbt, Airflow, Snowflake, CI/CD, and observability. Partners with People Analytics, Legal, Compliance, and business leaders to deliver secure, trusted workforce analytics and AI-enabled internal tools.

Lead and grow a data engineering team responsible for ingestion, transformation, orchestration, and serving layers. Ensure data quality, observability, cost-efficiency, and reliable SLAs. Build self-serve analytics substrate, define semantic layer and data contracts, implement engineering best practices, and partner cross-functionally with Data Science, BI, Analytics, and Product.

Design, build, and operate large-scale data pipelines and Spark/PySpark workflows; architect and evolve Samsara's data platform; build MCP servers and AI-agent tooling; optimize performance, ensure data quality and observability; mentor engineers and lead cross-functional projects to deliver scalable data products for analytics and business teams.

The Data Center Technician will be responsible for maintaining and managing the technical operations of the data center, ensuring optimal performance and reliability of IT systems.

Lead architecture and buildout of a new graph-backed enterprise data platform. Design ingestion, ETL/ELT pipelines, entity resolution, graph and relational storage, temporal models, governance, APIs, and containerized deployments. Partner with product and engineering to deliver production-ready graph traversal APIs, connectors, and observability for resilience analytics and downstream ML systems.

The Senior Data Engineer will develop and maintain end-to-end data pipelines, manage data integration, and work with varied data sources to enable analytics and drive customer success.

Leads technology vision, architecture strategy, engineering standards, and modernization for client reference data and markets fulfillment platforms. Advises senior leadership, resolves complex enterprise challenges, designs scalable and resilient data solutions, and advances AI-enabled, secure, compliant architectures. Responsibilities include data modeling, replication, metadata management, master data processing, identity resolution, integration, and adoption of emerging technologies across financial services portfolios.

Client-facing Solutions Architect designing and delivering scalable cloud, data, and AI-enabled solutions. Lead end-to-end projects, advise clients on technology strategy, ensure scalable/resilient architectures, mentor teams, drive delivery using agile methods, and collaborate globally to translate business needs into practical data solutions.

Design, build, and operate privacy-first People data pipelines and models. Ingest and standardize HRIS/People systems, ensure data quality and observability, implement access controls, and deliver trusted datasets, dashboards, and self-serve products for People leaders and executive reporting.

The Manager, Data Engineering will lead the data engineering team, oversee data architecture projects, ensure data reliability, and foster a culture of learning.