Top Senior Data & Analytics Jobs in Sacramento, CA

Lead a team of data engineers and analysts, define the data engineering roadmap, oversee data infrastructure, ensure analytics delivery, and establish data governance standards.

As a Director in the Data & Analytics team, you will lead client engagements, manage projects, develop strategies, create proposals, and mentor team members in data-driven initiatives.

As a Technical Solutions Manager, you'll onboard Enterprise customers onto Medallion's platform, focusing on data migration, integration, and automation for enhanced operational efficiency.

The Data Architect will design scalable data solutions, enforce data standards, lead architecture discussions, and collaborate with stakeholders. Responsibilities include managing platforms, ensuring data compliance, optimizing pipelines, and guiding teams toward data-driven solutions.

Perform geospatial wildfire hazard and risk modeling using fire behavior software and GIS. Calibrate fuelscapes and vegetation/canopy fuel layers, support nationwide risk assessments, translate fire workflows into software user stories, and collaborate with developers to test and deploy Wildfire Risk datasets.

Lead BI developer owning end-to-end reporting for marketing verticals. Build and standardize dashboards, model complex/third-party data (LookML), partner with Yield, Paid Media, and Account Management to deliver actionable analyses that optimize campaign performance, conversion, and revenue.

The Principal Data Platform Engineer leads the architecture and delivery of data platforms using Databricks, focusing on data pipeline design and client relationships.

Lead the technical roadmap and hands-on development of a scalable data platform, build analytics and data access solutions, ensure data quality/governance/observability, mentor and grow a team of data engineers, collaborate cross-functionally, and evaluate new big-data technologies.

The Senior Data Scientist will lead innovative data science efforts, leveraging advanced analytics, visualization, and insights from complex datasets to boost productivity.

Design, optimize, and scale Snowflake-based data architecture and pipelines. Implement data observability, operationalize MLOps, build semantic enterprise models, and deploy AI-assisted agents and automation for production analytics and commercial data products. Share cross-functional ownership for pipeline resilience, monitoring, and model lifecycle management.