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

Lead analytics for Udemy Japan partnerships: build and maintain KPIs and dashboards, perform in-depth business and partner analyses, support forecasting and partner-facing events, and provide data-driven insights to sales, leadership, and global partner operations to drive regional revenue growth.

The Data Scientist in Finance will analyze financial data, create dashboards, collaborate on data engineering, and find improvements for the business.

The Senior Business Intelligence Analyst will provide analytical support across various departments, focusing on billing and subscription analytics, to inform decision-making and improve business outcomes through data-driven insights.

The Senior Data Engineer will transform real-world data into analytics-ready datasets, build scalable pipelines, and conduct analyses to support scientific and business decisions, collaborating closely with data science teams.

Design and operate scalable data systems for People Analytics, ensuring reliability and privacy of sensitive employee data. Collaborate with leadership to create data products for decision-making.

Lead Retail GTM analytics and territory operations: build reporting, automate workflows, design territory models, manage data quality/enrichment, and deliver decision-support tools across Salesforce, Snowflake, and Sigma to scale sales coverage and drive growth.

Own and evolve the data lake and analytics stack powering fleet observability. Build and maintain scalable ETL/ELT pipelines, operate data lake infrastructure (Iceberg, Trino, Airflow, Spark, Superset), produce analytics and executive reporting, create dashboards and runbooks, and implement data governance and observability.

Build and maintain analytical data models, dashboards, KPIs, and self-serve analytics for Revenue. Partner with Data Engineering and cross-functional teams to enable GTM analytics, forecasting, attribution, data quality, and governance while scaling the analytics function.

Lead end-to-end design and delivery of analytics solutions that extend the Aladdin platform. Build end-to-end analytical applications using Python, databases and AI; prototype solutions, partner with product and tech teams, influence senior stakeholders, mentor peers, and translate investment challenges into scalable tools for portfolio analysis, sales, and client engagement.

Lead and grow a data engineering team, define data platform architecture and reliability (warehouse, ingestion, transformations, orchestration), set engineering standards, partner cross-functionally to support analytics and ML, and translate technical decisions for executive stakeholders.