Top Data Engineer Jobs in San Francisco Bay Area, CA

As a Data Engineer, you will design, implement, and maintain data systems for Notifications at Whatnot, ensuring data quality and performance while collaborating with cross-functional teams on data architecture and workflows.

Lead design and implementation of data architecture, ETL/ELT pipelines, data models, warehouses and lakes. Ensure data governance, security, cloud deployments, performance and cost optimization. Coach and manage team members, partner with stakeholders, and drive data-driven solutions for clients.

Lead design and implementation of enterprise data architecture and cloud-based data solutions. Manage large data engineering projects, develop data models and pipelines, ensure governance and security compliance, advise clients strategically, and build high-performing inclusive teams.

Design and implement data architecture and scalable ETL/ELT pipelines on cloud platforms (AWS/Azure/GCP). Analyze complex problems, mentor junior staff, ensure data governance/security compliance, liaise with stakeholders, and deliver high-quality client solutions while developing technical and client-facing skills.

Design and implement scalable data models and ETL pipelines (batch and streaming), ensure data quality/SSOT, collaborate with product and platform teams to resolve issues, contribute to data governance, and explore practical integrations between data engineering and AI.

As a Senior Data Engineer, you will automate processes, optimize data handling, build data products, and govern data while mentoring junior engineers.

The IT Controls Data Engineer will create and maintain data pipelines and automated evidence workflows for IT controls, ensuring compliance and audit readiness.

The role involves structuring and ingesting customer data, setting up ETL pipelines, and providing solutions for data export and import.

The Scientific Data Engineer will design data architecture, build ETL/ELT pipelines, implement data quality checks, and develop semantic layers for AI-consumable data products in healthcare research.

Build and operate production data pipelines integrating ERP/ATS/project management/telemetry into a queryable layer. Own the data model for a live knowledge graph. Ship SLA-backed datasets/services for tools and ML. Convert unstructured vendor/field data (PDFs, spreadsheets) into trusted structured inputs. Ensure data quality via tests, monitoring, and lineage, and use modern data stacks and LLM tools responsibly.

The Data Engineer will design and manage data pipelines, develop datasets for product metrics, and collaborate with teams to ensure robust data integration and processing.

Lead design and implementation of a scalable Big Data Audience Management platform (500+ TB). Own data pipelines (ingest, validation, transformation, storage) using Spark and Scala, mentor engineers, perform R&D on new technologies, and partner with product managers to meet roadmap and business needs.

Own and scale ReadyOn's data platform: design/build real-time and batch pipelines, implement ingestion and transformation workflows, model schemas in Snowflake and PostgreSQL, ensure observability and data quality, build connectors and feature-store roadmap, and provide technical leadership and mentorship across data, AI, and backend teams.

Design, implement, and maintain scalable data infrastructure and real-time processing for analytics platforms. Migrate systems from AWS to on-prem Kafka/Spark, implement data transformations, support production, optimize pipelines, query and analyze data, and build scripts and APIs to operationalize data science work.

Own and build the end-to-end data layer: extraction pipelines from messy supplier emails and PDFs, the unified data model, reliable observable pipelines, and ML-driven extraction evaluation. Drive extraction accuracy, data quality, lineage, monitoring, and automation to scale coverage and enable engineering and product to depend on the data layer.

The Data Engineer will support Data Analytics and Business Intelligence efforts, developing data pipelines, ensuring data performance, and collaborating within Agile frameworks to meet complex requirements for federal clients.

The Data Engineer will build and scale Baseten's internal data platform, designing data models and pipelines while enabling self-service analytics and ensuring data reliability.

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

Lead architecture, build, and maintain scalable people-data platforms and pipelines. Establish data quality frameworks, governance, lineage, and data contracts. Drive consistent modeling, monitoring, and schema evolution. Lead cross-functional initiatives, mentor engineers, and collaborate with analytics, data science, and HR to enable recruiting, workforce planning, and employee lifecycle insights. Advocate emerging data technologies and integrate AI to improve workflows and impact.

Architect and build high-scale product telemetry and lakehouse data solutions. Lead cross-functional initiatives, implement data contracts, enforce data quality, lineage, governance, and mentor senior engineers to drive reliable, scalable product analytics.

As an Analytics Engineer, you will create scalable solutions for data reporting, build data pipelines, and establish high data integrity standards while collaborating with multiple teams.

Design, build, and optimize data pipelines and models on GCP to support analytics and reporting. Partner with stakeholders to define KPIs, document best practices, and improve data discoverability and governance. Create user-friendly analytics products and visualizations; support data scientists, analysts, and business stakeholders. Communicate project progress, risks, and deliverables.

Build and maintain data pipelines to ingest, normalize, and deliver messy healthcare data (FHIR, HL7, CCDAs, PDFs) into structured models for AI and clinical use. Implement ETL, real-time webhooks, document extraction, PII sanitization, storage on AWS, and monitor data quality while ensuring compliance with healthcare interoperability standards.

As a Data Engineer at Figma, you'll build and maintain scalable data pipelines, optimize data models, and collaborate with teams to ensure timely data delivery.

Build, model, and maintain scalable BigQuery-based data solutions on GCP. Implement performant data models, storage partitioning/clustering, ETL improvements, data validation, and documentation. Collaborate with architects, data scientists, and engineers to deliver governed, high-quality data for reporting and AI initiatives.