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

The Senior Payments Pricing & Operations Analyst role involves supporting sales teams, analyzing payments data, improving operations, and mentoring junior staff while utilizing tools like Salesforce and SQL.

The Data Engineer will build real-time data pipelines for pricing algorithms, collaborate with teams, and contribute to batch data workflows.

The Business Analyst will manage the Quote-to-Cash lifecycle, liaising between IT and functional teams, and ensuring successful implementation of system updates while documenting requirements.

Lead analytics work translating complex healthcare data into decision-ready insights. Own KPI definitions, Snowflake data marts with dbt, executive dashboards in QuickSight, and cross-functional analyses to inform strategy, product, and operations.

The Senior Portfolio Lead will oversee data management services for clients, ensuring quality deliverables, strategic oversight, and optimal clinical data flows, while leading cross-functional teams and managing complex client relationships.

The Analyst II will leverage data analytics to derive insights, optimize credit strategies, and collaborate with cross-functional teams including Machine Learning and Engineering.

The Associate Manager will provide category insights, develop strategic recommendations, and collaborate with teams to drive growth for Warehouse categories. Responsibilities include data analysis, planogram creation, and joint business planning.

Lead digital measurement strategy for web and digital marketing. Build and maintain dashboards, integrate multi-platform data, perform tagging QA, run A/B test analyses, and deliver insights to optimize campaign effectiveness, UX, and ROAS.

This role oversees the design and evolution of finance reporting solutions using Power BI, collaborating with global finance teams to create scalable analytics and insights.

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.