Top Staff Data Engineer Jobs in San Francisco, CA

This role involves defining data reliability strategies, establishing company-wide standards for data quality, and leading cross-functional data engineering initiatives at Circle.

Lead architecture and delivery of scalable data infrastructure: design and optimize ETL/ELT pipelines, enterprise data models, and data quality frameworks. Define platform standards, mentor engineers, drive cross-functional initiatives, and partner with analytics, data science, and engineering stakeholders to ensure reliable, production-grade data assets.

Lead architecture and delivery of SoFi's data platform: build scalable data pipelines, drive cloud-native and AI-enabled tooling, enforce governance and security, mentor senior engineers, and support production on-call.

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.

Lead the architecture and development of robust data pipelines and backend services for MLS data, integrating AI solutions and ensuring data quality.

Lead architecture and implementation of scalable data pipelines, integrations, and cloud data infrastructure. Own IaC (Terraform), workflow orchestration (near-real-time and batch), third-party API and AI/LLM integrations, data export pipelines, and internal tooling. Mentor engineers, drive technical strategy and cross-team priorities, and communicate tradeoffs to technical and non-technical stakeholders. Must work EST/CST hours and be authorized to work in the US.

The Senior Staff Data Engineer will design scalable data systems, lead technical direction, optimize data platforms, and ensure data quality and performance for Observability & Insights.

Design, build, and operate production ML systems that generate trusted signals for ranking, retrieval, recommendations, propensity/churn/LTV, and next-best-action decisioning. Define signal/data contracts, own feature and candidate generation through serving, experimentation, monitoring, and feedback loops, and evaluate long-term business impact, trust, fairness, and compliance. Partner across product, data, modeling, risk, and compliance and apply AI/agents to accelerate engineering and operations.

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.

Lead architecture, development, and operation of the company data and AI platform. Define technical strategy, build and mentor a high-performing data platform team, drive company-wide initiatives, deliver scalable multi-region data pipelines, oversee ETL frameworks, metrics stores, infrastructure and data security, and advocate best practices for lakehouse-style data processing and model governance.

Lead architecture and evolution of Headway's data platform (warehouse, ingestion, orchestration, CI/CD, monitoring, cloud infra). Serve as technical anchor across analytics, product, and ML teams, drive platform roadmaps, set standards, mentor engineers, and own end-to-end infrastructure decisions for scale and performance.

The Senior Staff Data Engineer will lead and influence data technology strategy across teams, focusing on infrastructure for data ingestion, storage, and analytics. Responsibilities include project execution, providing technical guidance, and ensuring reliability, performance, and security of data systems.

The Staff Data Engineer will lead the architecture and reliability of Hinge Health's data platform, manage technical complexity across teams, set data standards, and enhance engineering practices.

As a Senior Staff Data Engineer, you'll set the technical vision for data architecture, lead initiatives across teams, mentor engineers, and ensure platform reliability, while integrating data systems with ML pipelines effectively.

Design, build, and operate the core data warehouse, ingestion, orchestration, and cataloging platform. Develop batch and streaming pipelines, ensure data quality, governance, observability, and provide ML data platform capabilities. Lead architecture, improve platform reliability and performance, and collaborate with product, engineering, data science, security, and compliance teams.

Consulting role contributing to analytics and data management projects: gather and refine requirements, build documentation, estimate effort, perform data modeling, SQL-based validation and QA, train clients, support change management, and collaborate with engagement leads to prioritize work and ensure delivery.

Design, build, and operate production ML signal systems—ranking, retrieval, recommendations, propensity, and next-best-action—covering feature/candidate generation, serving, experimentation, monitoring, and feedback. Define signal contracts (freshness, provenance, confidence), evaluate long-term impact (trust, fairness, compliance), and partner across product, data, and risk teams to deliver reusable customer-intelligence capabilities.

As a Staff Data Engineer, you'll lead the data engineering team, own the Databricks platform, build production pipelines, and engage with stakeholders while driving architectural judgement and maintaining platform quality.

Lead design and delivery of large-scale data pipelines and warehouse systems. Define technical strategy, enforce data governance, improve developer efficiency, mentor engineers, and align data engineering efforts with business goals to enable analytics and ML at scale.

Lead design and scaling of enterprise data architecture and pipelines. Build and maintain ETL/ELT and CDC/streaming workflows, improve data quality and observability, own schema and warehouse modeling, implement governance (RBAC), and provide cross-functional technical leadership to enable trusted, scalable data for analytics and product teams.

Lead architecture and delivery of Boulevard's data platform, building foundational data models, pipelines, and customer-facing analytics. Collaborate with Product and Engineering to create scalable data products, Snowflake data sharing solutions, performant visualizations, and machine learning features (recommendations, forecasting, anomaly detection) to drive data-driven decision-making and product value.

Design, build, and scale reliable batch and real-time data pipelines and warehouses. Partner with engineering, data science, and business teams to define data models, improve observability, optimize storage and querying, and evangelize data engineering best practices across the company.

Lead architecture and implementation of scalable data systems and pipelines from ingestion to delivery. Own ambiguous, high-impact integrations, improve data quality and reliability, adopt AI-augmented engineering, mentor engineers, and collaborate with Product, ML, and customer teams to ship production solutions.

The role involves building scalable data platforms, developing data pipelines, mentoring engineers, and enhancing data security while collaborating across teams.

Own and evolve the data platform by leading architectural evolution, collaborating with teams for strategic data initiatives, and ensuring reliable data systems.