Top Data & Analytics Jobs in Sacramento, CA

Lead a team delivering actuarial statistical reporting, regulatory submissions, and analytics. Ensure compliance with bureau requirements, drive automated reporting and UAT for policy/claims systems (Guidewire, Solartis), partner with actuarial, technology, and vendors, and manage stakeholder/regulator interactions while mentoring staff and improving data governance and reporting processes.

Lead enterprise data architecture, migrations, and data services; define standards and roadmaps; oversee complex ETL and third-party integrations; deliver analytics, BI dashboards, and commercialization of AI analytics offerings; build the Data Strategy & Services organization and ensure continuity for legacy clients while partnering across Product, Engineering, Sales, and Customer Success.

Responsible for designing, developing, and maintaining scalable data pipelines and infrastructure, implementing data governance, and collaborating with teams to meet data needs.

Own operational health, governance, and integrity of GTM customer and prospect data across Salesforce, Marketo, Demandbase and integrated systems. Implement data quality programs, manage enrichment and integrations, troubleshoot sync failures, support segmentation and reporting, document standards, and enable scalable automation and AI workflows to support Marketing, Sales, Customer Success, and Analytics.

Organize and curate large volumes of raw information: extract key points from transcripts, maintain clean spreadsheets, curate links/resources, tag and categorize content, and follow or propose systems for information structure. Part-time remote role with initial 10 hours/week and potential to grow.

Transform operational and financial data into actionable insights to support vaccine purchasing programs. Build dashboards and reports, monitor manufacturer contract compliance, analyze purchasing and enrollment trends, support revenue optimization and rebate/commission reporting, maintain Salesforce data integrity, and drive process improvement and automation across cross-functional teams.

Lead technical design and implementation of cloud data pipelines and data warehouse models using PySpark, Snowflake, and AWS. Drive cloud migration, establish engineering standards, optimize performance, coordinate onshore/offshore teams, engage stakeholders, mentor junior engineers, and ensure delivery of insurance analytics solutions.

Design, build, and maintain scalable data pipelines, data lakes, and databases; ingest and map customer financial datasets; monitor pipeline reliability; translate business requirements into data flows and analytical insights to ensure high-quality, usable data.

Build and maintain ETL/ELT pipelines, ingest and transform structured and unstructured data, integrate APIs and external sources, improve data quality and monitoring, support dashboards and ML pipelines, optimize warehouse and cloud performance, and contribute to data governance and documentation.

Lead post-sales and revenue analytics by integrating product telemetry, support signals, and revenue data. Build scalable data models, reusable datasets, and semantic layers. Define SaaS metrics, forecast revenue and usage, predict expansion and churn, and deliver dashboards and insights to drive renewals, expansion, and revenue growth.