Top Lead Data Engineer Jobs in San Francisco, CA

Lead the design and implementation of a unified semantic layer and enterprise data models, transforming SAP, Workday, Salesforce, Anaplan and other sources into AI-ready datasets. Establish modeling standards, testing, observability, and automation; collaborate with engineers and business stakeholders to deliver scalable, high-performance data solutions for AI agents and analytics.

Lead integration and data migration workstreams for SaaS implementations. Document technical requirements, estimate effort, mitigate risks, deliver secure scalable integrations, perform data imports and quality checks, mentor the implementation team, and support pre-sales as needed.

The Data Architect/Data Governance Lead supports the Medicaid Enterprise Data Warehouse by leading data architecture, metadata management, and governance processes, ensuring compliance and scalability.

The Senior Data Engineer will design and manage petabyte-scale data pipelines, ensuring data quality and architecture for operational decision-making and ML training.

Lead the architecture and implementation of data integrations with healthcare payers, build data pipelines for AI/ML systems, and establish engineering best practices.

The Technical Lead will build software systems for AI-native drug discovery, design data pipelines, develop APIs, and collaborate with scientists to create efficient workflows and solutions.

Lead design and execution of data migration, archival, and disaster recovery for a cloud-based court case management modernization. Own migration strategy, data lifecycle and retention, DR/HA design and drills, tooling evaluation, documentation, and coordination with Data Engineering, Governance, Security, and stakeholders to ensure auditable, resilient, and compliant migrations.

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.

The Senior Data Engineer will build and deploy data pipelines, develop warehouse architectures, and design analytics solutions for the team.