Top Senior Data & Analytics Jobs in Sacramento, CA

Lead customer analytics to measure and improve campaign and product performance. Build scalable data models, dashboards, and reports; perform segmentation, cohort, forecasting, anomaly detection, and ad-hoc analyses; ensure data quality and rigorous QA; communicate insights and recommendations to technical and non-technical stakeholders.

The Deploy Engineer will onboard clients onto Ometria's product, ensuring data integration, validation, and client training, while maintaining platform reliability and establishing strong client partnerships.

Own and improve dbt models, ELT pipelines, and warehouse architecture (Snowflake or equivalent) to deliver reliable executive KPIs and metric governance. Build data spine for Finance/Operations, enforce data quality/testing, partner cross-functionally with Engineering, FP&A, and Accounting, and influence analytics engineering standards, tooling, and roadmap.

Lead customer-facing analytics: build dashboards, reports, and POCs that demonstrate ROI and utilization trends for healthcare provider data. Collaborate with data science and engineering on advanced models, assess and integrate new data sources, ensure data quality, and support presales and executive-facing storytelling.

The Senior Data Analyst will analyze digital marketing campaigns, leverage data sources for business decisions, and communicate insights effectively to improve performance and support Media Partners.

Own marketing channel performance tracking, reporting, and analysis. Design and analyze experiments (A/B, incrementality), build dashboards in Looker/Tableau, support LTV and forecasting models, identify measurement gaps, and translate analysis into clear recommendations for Growth, Marketing, and Finance stakeholders.

Design and deliver executive-ready Power BI reports, dashboards and agentic experiences. Build semantic models and self-service analytics, apply DAX, Power Query and Fabric notebooks, perform data exploration with SQL/KQL, and drive AI-enabled automation. Collaborate with data engineering to influence ingestion and transformation, translate business strategy into data solutions, and ensure performance, reliability, and scalability of reporting assets.

Lead end-to-end debit analytics: design and modernize reporting, build executive dashboards, run A/B tests, produce actionable insights, optimize measurement/KPIs, mentor analysts, and partner with stakeholders to influence product and business decisions using cloud data platforms and advanced SQL/Python analytics.

Design, build, and maintain scalable data lakehouse platforms and ELT pipelines. Improve engineering practices, develop automation/tooling, monitor performance, reduce costs, and support platform modernization across Azure and cloud data technologies.

Lead design and build of scalable cloud-native data pipelines (Databricks, PySpark) across Azure and GCP. Architect Snowflake/BigQuery warehouses, analyze healthcare datasets (FHIR, HL7, claims, EMR), enforce governance and security (Unity Catalog, Terraform, GitLab CI/CD), mentor engineers, and ensure HIPAA/HITRUST compliance.

Design, develop, and maintain advanced Power BI dashboards and data models. Build DAX measures and Power Query transformations, optimize performance, implement role-based security, integrate with Azure data platforms, support ETL/SSIS and scheduled refreshes, and provide documentation and training to stakeholders.

Lead design and implement enterprise-scale Azure Lakehouse platforms using Databricks. Build and optimize PySpark ETL/ELT pipelines, Delta Lake/Medallion architectures, and CI/CD deployments. Lead migration from legacy systems, ensure governance, security, performance tuning, and mentor engineers while collaborating with stakeholders to define data strategy and roadmaps.