Top Senior Data & Analytics Jobs in Sacramento, CA

Design, build, and operate production-grade data ingestion pipelines and dbt transformations into a Databricks lakehouse. Establish data quality, monitoring, and observability. Partner with Product and Engineering to enable metrics, dashboards, and longitudinal patient analytics supporting clinical and operational decision-making.

Serve as primary DBA SME bridging on-premises SQL Server to Microsoft Fabric. Design hybrid database architectures, implement cloud-based SQL services, establish Data Operations processes and SLAs, manage data integration, security controls, performance tuning, monitoring, and disaster recovery to support analytics and AI workloads.

Design and maintain company-wide dashboards, define KPI frameworks, implement tracking and data governance, write advanced SQL, partner with product and engineering, build predictive/AI-ready data layers, automate reporting, and present insights to leadership to drive operational and financial improvements.

The Senior Data Engineer will scale and evolve the data platform, develop ETL/ELT pipelines, establish best practices, and optimize systems for performance while collaborating with various teams.

The Data Engineer is responsible for designing data workflows and pipelines, implementing systems engineering principles, and deploying data streaming technologies while ensuring compliance with industry regulations and best practices.

The Sr. Data Engineer - Databricks designs and maintains scalable data solutions using Apache Spark and Databricks, ensuring data quality and performance for analytics and reporting.

The Senior Data Engineer will design, build, and support data environments, orchestrate pipelines, and implement data solutions for advanced analytics and machine learning, working closely with project teams.

The role oversees analytical characterization and comparability studies for biologics, ensuring regulatory compliance and leadership in product development.

The VP Global Grid Modeling will lead global data strategy, manage high-performing teams, ensure quality datasets, and engage with customers for insights in energy markets.

Build and maintain automated ETL/ELT data pipelines, improve data quality and monitoring, optimize Postgres and BigQuery schemas and queries, develop internal tooling, support data governance (HIPAA), participate in on-call rotation, and collaborate across engineering teams to scale data systems.