Top Data & Analytics Jobs in Sacramento, CA

Design and build Snowflake transformation layer and migrate legacy SQL to versioned dbt models. Define conformed dimensions/facts using Kimball principles, set modeling and CI/CD standards, implement data quality/lineage, support BI migration and AI/ML readiness, and mentor future hires. Hands-on work in dbt, SQL, and Python with stakeholder collaboration and governance for financial and operational data.

Build and own the data platform backbone: design ingestion patterns, Snowflake warehouses, governance, and freshness strategy. Implement reliable batch and streaming pipelines, data quality, observability, and onboarding processes. Lead legacy migrations, create data contracts and SLAs, and apply AI-native tooling to automate debugging, documentation, and operational workflows while partnering with Analytics, Engineering, and vendors.

Build and maintain CS reporting, dashboards, and health score models to identify renewal risk and inform strategy. Deliver executive reporting, collaborate cross-functionally to improve data quality, and develop predictive analytics and longitudinal tracking to reduce churn.

Own the companys end-to-end data graph, ensure data quality and lineage, and deliver Sigma dashboards and client-facing reports. Act as single owner for triage, prioritization, and translation of business questions into actionable insights, partnering closely with data engineering and business leaders to set standards for production-ready reporting.

Design and own a federated, multi-institution medallion lakehouse on Azure Databricks and Microsoft Fabric. Define federated multi-tenant architecture, Unity Catalog security, data ingestion from ERP/SIS/LMS/CRM/Workday, and platform standards. Provide hands-on architecture guidance, review designs, document decisions, and partner with governance, delivery, and engineering teams to enable production analytics at multiple institutions.

Audit and reconcile marketing and lead data end-to-end, maintain campaign tracking and platform integrations, troubleshoot data flow issues, manipulate large datasets to identify discrepancies, coordinate with vendors and stakeholders, and recommend process improvements to ensure accurate marketing-to-intake reporting.

Transform commercial, market, consumer, and portfolio data into actionable insights. Build and maintain dashboards and KPI reporting, analyze performance and competitive trends, support pricing, assortment, and launch decisions, and deliver executive-ready recommendations while partnering with cross-functional teams to ensure data quality and commercial alignment.

As a Senior Data & Analytics Engineer, you'll lead data initiatives, manage a team, and ensure data quality while turning insights into actionable decisions across the company.

Manage daily Data team operations, research and analyze datasets, build internal and external reports (including an annual Startup Ecosystem Ranking), and maintain/improve Python scripts and data infrastructure to deliver actionable insights.

Own client-facing analytics and attribution: establish baselines, implement tracking and lead-to-sale matching, run holdout and lift experiments, quantify cost avoidance, build cross-client benchmarks, and translate findings into clear ROI narratives that inform pricing, product, and renewal conversations.