Top Senior Data & Analytics Jobs in San Francisco Bay Area, CA

Designs and maintains scalable data pipelines and infrastructure, establishes data governance and quality standards, and drives technical decisions across Headway’s data platform. Partners with Product, Engineering, Analytics, Data Science, Finance, and Infrastructure to evolve data architecture, optimize performance, implement infrastructure-as-code, and ensure reliable, traceable data for AI-powered tools.

Provides analytics and strategic advisory support for mergers, acquisitions, and other business transactions. Analyzes contract data to identify risks, obligations, performance insights, and compliance indicators; develops algorithms, data models, pipelines, dashboards, and predictive models using Python and machine learning. Collaborates with clients and internal teams, validates data integrity and security, mentors junior staff, and delivers data-driven recommendations.

Build scalable, secure GCP data pipelines and reusable frameworks supporting machine learning and AI workloads. Develop Python, Go, SQL, and Beam transformation libraries; implement orchestration, data modeling, feature stores, semantic layers, governance, quality, lineage, and observability. Optimize workload performance and costs, migrate models to GCP, and partner with data scientists. The role also includes documentation, workshops, CI/CD integration, and occasional off-hours production support.

Analyze complex data and develop managed data solutions, business intelligence tools, dashboards, metrics, and self-service capabilities. Partner with business and technology teams to deliver strategic insights, manage data quality, metadata, lineage, security, and access governance. The role requires scripting, querying, visualization, Snowflake development, and familiarity with cloud services and data governance.

Design, develop, deploy, and operate scalable ELT pipelines and data architectures for developer experience products. Integrate and validate diverse data sources, improve pipeline and query performance, establish data governance and quality practices, and build reliable data sources for proactive recommendations. Collaborate with data scientists, analysts, engineers, product managers, and customers while mentoring teams and promoting scalable data engineering standards.

Design and build maintainable data pipelines, ETL processes, and data architecture standards. Collaborate with product managers, analysts, and machine learning engineers to translate requirements into automated, scalable solutions. Apply software engineering best practices, asynchronous systems, APIs, streaming, testing, monitoring, and Python and SQL expertise. Help prioritize data initiatives based on business impact and communicate complex technical concepts to technical and non-technical stakeholders.

Own front-end tracking, reporting, dashboards, and analytics for marketing websites and growth funnels. Analyze performance, conduct ad hoc investigations, and deliver actionable recommendations to digital and web marketing stakeholders. Lead A/B testing and experimentation, interpret statistical results, support tracking and dashboard documentation, and collaborate with developers and analytics teammates. Translate business questions into technical requirements while helping marketing teams improve leads, pipeline, revenue, and ROI.

The Economist will analyze travel and spending data to identify trends, craft insights, and present findings, serving as an economic advisor to leadership.

The Analytics Engineer will analyze sales proof-of-concepts and self-service trials, support growth and product-led sales initiatives, and evaluate pricing and monetization strategies. The role partners cross-functionally, models data in dbt, maintains data warehouses and ELT pipelines, experiments with emerging data and AI tools, and trains teammates on effective data workspace practices.

Leads the data engineering team, including hiring, coaching, technical direction, platform architecture, data pipelines, Snowflake warehousing, governance, quality, observability, and incident support. Partners with Data Science, Analytics, Clinical Operations, Biostatistics, and Business Development to deliver trusted data products for clinical operations, asset evaluation, reporting, and machine learning. Oversees budgeting, resourcing, documentation, technical programs, and responsible use of AI engineering tools.