Top Remote Data & Analytics Jobs in Sacramento, CA

Design, build, and maintain scalable Databricks-based data pipelines and ELT workflows; develop and document dbt models; define data modeling methodology; ensure data quality, reliability, and scalability; collaborate with clients and cross-functional teams; provide technical guidance and deliver improvements to clients' data infrastructure and analytics capabilities.

Conduct client-facing analysis of POS and retail sales data to produce strategic insights. Scope research, write SQL and Python scripts to extract and analyze large datasets, create executive-ready deliverables, and serve as a power user of Bolt to improve and evaluate AI-driven analytics. Partner cross-functionally and manage client expectations throughout projects.

Manage client data reconciliation projects by establishing broker data connections, preparing and verifying large datasets, troubleshooting broker feeds, responding to inbound client queries via Salesforce ServiceCloud, demonstrating services and identifying cross-sell opportunities, and supporting ad-hoc operational projects to improve team effectiveness.

The Senior Data Analyst will drive product insights through analyses, support A/B testing, and develop reporting to enhance product growth and user acquisition.

The role involves creating impactful HR technology research, analyzing data governance, engaging clients, and mentoring team members, focusing on AI's influence in HR.

As a Principal Data Scientist, you'll drive data-driven strategies across Growth and Membership Operations, integrating AI tools and managing complex data systems to enhance operational performance.

The CX Automation Performance Analyst manages post-launch AI programs, ensuring ongoing performance and optimization, building dashboards, and maintaining documentation.

As a Senior Data Engineer, you will manage data pipelines, ensure data quality, partner with teams for data-driven decisions, and improve the data platform while maintaining data integrity.

As a Curriculum Manager, you will manage the content development lifecycle, collaborate with instructors, and improve data science curriculum, ensuring technical accuracy and pedagogical effectiveness.

Design and maintain enterprise data architecture and lakehouse solutions. Lead data migration, integration, governance, and BI enablement. Define strategy, implement pipelines, ensure data quality, security, and provide technical leadership and mentoring.