Top Data Engineering Jobs in San Francisco, CA

Designs and maintains production data pipelines, dbt models, Airflow DAGs, and People data products using Snowflake and Workday data. Ensures data quality, observability, governance, row-level security, and reliable ETL/ELT operations. Builds semantic models and AI agents, partners with analysts and stakeholders, translates requirements into deliverables, communicates technical trade-offs, and mentors engineers. Supports recruiting, compensation, talent management, and learning and development analytics.

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.

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.

Leads data-driven digital product and service improvements, manages transformation programs and project portfolios, develops digital talent, oversees quality and budgets, and directs team performance. The role shapes digital strategy, supports product management processes, drives cybersecurity incident remediation, and builds organizational capability through coaching, collaboration, and leadership.

Supports enterprise asset management data migration and systems integration initiatives involving IBM Maximo. Analyzes source and target data, executes migration strategies, develops integration objects and interface components, validates exchanged data, performs quality reviews, and coordinates project workstreams. The role requires expertise in Maximo Integration Framework services, data governance, data management standards, enterprise platform integration, and large-scale integration programs.

Lead an eight-person Analytics Engineering team and set the strategy for trusted, AI-ready self-service data. Own semantic models, governed metrics, data modeling, BI tools, LLM-powered data access, evaluation and telemetry systems, and production data applications. Establish governance, security, testing, deployment, and monitoring standards; define the long-term roadmap; partner cross-functionally; and hire, coach, and retain a high-performing team.