Top Data & Analytics Jobs in Sacramento, CA

Lead account-level analytics strategy by translating client objectives, media performance, and cross-channel data into measurement plans, testing roadmaps, dashboards, and actionable recommendations. The role requires client-facing data storytelling, BI and SQL proficiency, quantitative analysis, quality control, and collaboration with media and strategy teams to improve marketing decisions and measurement effectiveness.

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.

Build and scale resilient ingestion, catalog, and derived data pipelines powering core infrastructure datasets. Own data contracts, schema governance, quality gates, automated testing, observability, and pipeline reliability. Modernize legacy systems into scalable platform architecture, including a graph database layer. Partner with global engineering, data science, ML, intelligence, and trust teams to support matching, confidence scoring, and automated workflows.

Leads a multidisciplinary marketing analytics organization spanning data engineering, analytics engineering, visualization, and data science. Builds attribution, ROI, customer journey, predictive signal, data governance, and AI-ready information architecture systems. Partners with Sales, RevOps, Finance, PLG, and Data teams to improve capital allocation and growth decisions. Oversees executive dashboards, metric alignment, team capacity, and strategic analytics delivery.

Build and operate production pipelines for legal records from PACER, court systems, opinions, PDFs, scans, XML, and HTML. Develop LLM-assisted extraction workflows, validate data quality, optimize SQL, and support RAG and semantic search products. Manage AWS S3 and RDS systems within security guardrails while collaborating with engineering teams. The role requires strong Python and SQL skills, legal data experience, document extraction expertise, and autonomous problem-solving with large, messy datasets.

Architects, administers, secures, and optimizes enterprise database and infrastructure platforms supporting Navy readiness, training, and analytics systems. Leads database architecture, ETL/ELT pipelines, performance tuning, high availability, disaster recovery, virtualization, monitoring, cybersecurity compliance, vulnerability remediation, and access controls. Coordinates system changes, configuration management, interoperability, technical reporting, demonstrations, and training-material updates with Government, development, cybersecurity, and training stakeholders.

Leads digital and marketing analytics for customer acquisition across multiple lending brands. Owns performance reporting, measurement frameworks, data governance, attribution and marketing effectiveness models, funnel analytics, experimentation, dashboards, and executive insights. Partners with Marketing, Risk, Finance, Operations, Technology, Engineering, and Data teams to optimize conversion, ROI, customer journeys, and data infrastructure. Requires advanced SQL, web analytics, statistical analysis, experimentation, and marketing measurement expertise.

Leads analytics, reporting, data modeling, automation, AI-agent development, and quality assurance for revenue cycle operations. Creates Power BI and Excel reports, analyzes complex healthcare and operational datasets, develops scalable warehouse models, and delivers actionable insights to leadership. Uses SQL, cloud data platforms, Git, Python, and AI-assisted tools to improve reporting efficiency, accuracy, and decision support.

Develop and maintain reports, dashboards, KPIs, and executive insights using SQL, Power BI, and other BI tools. Reconcile operational and financial data, investigate anomalies, ensure reporting quality, and document data models, metadata, governance, and reporting inventories. The role also performs advanced data manipulation, visualization, data storytelling, and analytical recommendations. Fraud and disputes domain knowledge is preferred.

Build and steward Netflix advertising quality-of-experience data, from device telemetry and instrumentation through data pipelines and dashboards. Collaborate with product engineering, data engineering, and data science teams to measure user-perceived performance, improve data quality, document user flows, and establish monitoring and measurement best practices. The role requires strong SQL and Python skills, technical communication, stakeholder management, and comfort working independently in an ambiguous environment.