Top Data Engineering Jobs in San Francisco, CA

Contract Marketing Data Analyst to clean and rebuild marketing data models, integrate ad/analytics and conversation data into Snowflake, own dbt + Sigma layers and dashboards, implement quality-control/health monitoring, align GTM data models, and produce a plain-language data dictionary for team and LLM use.

Lead and grow data engineering teams to build a scalable, AI-ready data platform with strong governance. Partner with Product, Analytics, Data Science, and Marketing to deliver trusted data products, drive data quality, CI/CD, and operational reliability, and prioritize high-impact work while fostering technical excellence and innovation.

The Senior Data Engineer will design, implement, and maintain data infrastructure and ETL pipelines, optimize data flow, and develop reporting solutions. They will collaborate with teams to enhance data quality and support data-driven decision-making.

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.

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.

Technical lead embedded with product engineering to own telemetry contracts and instrumentation, design and operate experimentation/A-B testing infrastructure, build catalog/content integrations, design semantic models, maintain external reporting pipelines, operate analytics feedback loops, mentor mid-level engineers, and provide on-call leadership for product-tier data pipelines.

Lead and grow a team of analytics engineers to build a centralized, AI-ready data foundation. Own Snowflake+dbt platform roadmap, semantic/metrics layer, data modeling, quality, observability, and stakeholder partnerships to deliver trusted, scalable data products and drive AI-enabled experiences.

Lead a newly formed data engineering team to standardize data practices, drive cross-functional AI-driven initiatives, and provide hands-on guidance in SQL optimization, data modeling, and the GCP data/streaming stack while balancing people management and technical leadership.

Design, build, and maintain end-to-end data pipelines and models to support CX operations, compliance reporting, and customer insights. Partner with stakeholders to deliver self-serve analytics, dashboards, and trusted metrics while driving data quality, governance, and automation.