Top Remote Data & Analytics Jobs in Sacramento, CA

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.

Lead end-to-end COGS and gross margin analysis for hardware and software products, model cost-saving scenarios, answer ambiguous executive questions, partner with data engineering/finance/product, build reliable datasets and analytical frameworks, and present recommendations to C-suite stakeholders.

Own SQL and dbt-based data modeling and data quality for clinical and claims datasets. Author and refactor dbt models/tests, triage DQ alerts, design monitors, optimize SQL performance, and collaborate with Data Engineering and stakeholders to ensure trusted production datasets.

Lead Finance Data & Analytics to build trusted data sources, governance, and analytics for Finance and cross-functional stakeholders. Manage analysts, drive data strategy and Snowflake data models, produce insights via SQL and Tableau, and deploy AI solutions to optimize finance decision-making and operations.

The Senior Data Analyst oversees performance reporting tools, automates data pipelines, conducts quantitative analyses, and communicates findings to various stakeholders.

Lead statistical analysis for clinical studies in oncology and cardiology, provide project leadership, and mentor junior biostatisticians while ensuring regulatory compliance.

Build and scale the analytics foundation: own dbt projects and Snowflake warehouse, create trusted datasets and semantic layers for AI, build ELT pipelines from APIs, implement testing/observability and CI/CD, design reconciliation models, enable stakeholder self-service, and partner cross-functionally to drive data-driven decisions across GTM, Product, Finance, People, and Operations.

Build, deploy, and operate production-grade data pipelines and data products for healthcare audiences. Design transformations, data models, and governed views using Python, SQL, Airflow, S3, Snowflake, and EMR. Implement data-quality, monitoring, and privacy-by-design controls for PHI/PII. Partner with product, analytics, and platform teams to onboard sources, support audience discovery, segmentation, activation, measurement, and troubleshoot production issues.

Own end-to-end product analytics: define questions and success metrics, run A/B tests, build dashboards and reusable SQL/Python analyses, investigate performance changes, and collaborate with Product, ML, and Data teams to inform product decisions.

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.