Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Design and implement data integration and data warehouse solutions using big data technologies. Build cost-efficient, performant cloud data pipelines, apply data modeling and machine learning knowledge, and implement real-time streaming and aggregation patterns.

Design, build, and operate a secure, scalable Generative AI platform on AWS (including Bedrock) to support production LLM applications in regulated financial environments. Own platform lifecycle: architecture, deployment, operations, monitoring, incident management, reliability, and performance. Implement LLM inference, RAG, Agents, guardrails, observability, security controls, access management, compliance, and cost optimization. Provide production support, reliability engineering, and AI governance.

Lead onshore data engineering/solution lead responsible for hands-on implementation, mentoring junior developers, and managing onshore/offshore teams. Build ETL and data warehouse solutions using Azure (ADF, Synapse), Databricks, PySpark/Python and SQL. Create design artifacts, source-to-target mappings, and specification documents; able to work from client office locations.

Design, configure and implement ServiceNow HRSD solutions including case management, portals, integrations, workflows, forms, reports, ACLs, and monitoring. Collaborate with HR product owners, business users, and IT teams to deliver secure, scalable global employee experience and provide technical leadership, documentation, code reviews, and troubleshooting.

Serve as a Workday functional SME for Finance and HR: gather client requirements, configure Workday Financials and HR modules, conduct testing and UAT, lead training, provide post-implementation support, perform fit-gap analysis and change management, document solutions, and collaborate on integrations and project delivery.

Senior hands-on Cloud Data Architect responsible for designing scalable, secure Snowflake-based data platforms and lakehouse solutions, enabling enterprise analytics and AI-native applications. Lead architecture, create design artifacts and blueprints, define scope and sizing, translate business requirements into technical solutions, collaborate with security and data teams, mentor junior staff, and guide implementation.

Develop, test, and maintain applications using Java, Python, or Node.js. Write clean, efficient code, debug and optimize, collaborate with cross-functional teams, use data structures/algorithms, work with SQL/NoSQL databases, participate in code reviews, and stay current on AI/ML concepts, agents, and automation tools.

Design, build, and optimize end-to-end ETL/ELT pipelines using Python and PySpark for large structured and unstructured datasets. Ensure data quality through validation and reconciliation, troubleshoot performance issues, implement CI/CD and code review practices, and collaborate with IT and business stakeholders to translate requirements into scalable data solutions.

Manage client project plans and budgets, ensuring alignment with client requirements, while leading Agile ceremonies and promoting best practices. Requires technical knowledge and project management skills to address challenges and enhance collaboration.