Top Data & Analytics Jobs in Sacramento, CA

Leads analytics and data engineering for Sales and Revenue Operations. Builds reporting in Looker and Snowflake, manages CRM data flows into cloud warehouses, establishes transformation and modeling layers, and develops forecasts, scoring, churn, and expansion models. Supports territory, quota, pricing, and revenue-truth initiatives while presenting insights to finance and company leadership.

Analyze product, user, transactional, and repayment data to develop risk and underwriting models, reduce losses and fraud, monitor model performance, and guide product and growth strategy. Build Looker dashboards and LookML models, conduct segmentation and experimentation, measure CAC and LTV, and communicate actionable insights to product, engineering, marketing, finance, and leadership.

Supports enterprise data governance and business intelligence initiatives by profiling datasets, defining quality rules, validating metadata and lineage, maintaining business glossaries, and testing API integrations. Develops data-quality scorecards, governance reports, dashboards, documentation, and training materials. Collaborates with data owners, stewards, engineers, and government stakeholders while tracking remediation and testing evidence in Azure DevOps. The role requires Power BI, data governance, data-quality, SQL, ETL, and relational database experience in a Navy environment.

Manages program data by cleaning, updating, validating, and preparing datasets for analysis. Monitors data integrity across systems, resolves collection issues, identifies data-quality trends, supports visualizations and form configuration, and maintains documentation. Collaborates with stakeholders on project and platform maintenance activities while adapting to changing priorities. Requires R data manipulation, basic descriptive statistics, online survey-form development, digital fluency, strong attention to detail, and independent task management.

Lead ownership and evolution of a Microsoft Fabric-based data platform: design medallion/semantic architectures, build and optimize data pipelines, enable Power BI reporting, support SQL Server performance and API integrations, implement observability with Azure Log Analytics/KQL, and shape the data+AI roadmap.

Build and maintain data pipelines for network and operational telemetry, integrate DataMiner and other monitoring systems, create Power BI dashboards, configure monitoring metrics and alerts, automate reporting, analyze network performance and recovery events, and translate technical findings into actionable insights for technical and executive stakeholders.

Leads Wiley Research’s commercial analytics strategy, including KPI frameworks, executive dashboards, competitive intelligence, performance measurement, data governance, and scenario modeling. Advises executive and board-level leaders, aligns Finance and commercial reporting, consolidates fragmented data practices, and builds a trusted analytics capability across global teams. The role also develops analytical talent, drives self-service reporting, and translates complex findings into strategic decisions concerning growth, retention, investment, and market performance.

Leads client measurement strategy, analytics audits, tracking implementations, QA, data modeling, attribution, CRO experimentation, privacy compliance, and migration analytics. Presents actionable findings to clients, partners across delivery teams, and helps grow the agency’s analytics practice through standardized processes, tooling, AI adoption, and sales support.

Designs and maintains scalable Databricks data pipelines on AWS, covering ingestion, transformation, streaming, data quality, and analytics-ready dataset delivery. Builds medallion architecture layers using Spark, Python, SQL, Delta Lake, and AWS services. Responsibilities include source-to-target mapping, unit testing, CI/CD deployment, anomaly analysis, and compliance with FISMA High and multi-tenant governance requirements. Collaborates in Agile teams and uses AI automation tools to accelerate pipeline development and validation.

Designs and operates data infrastructure for a clinical trial platform. Builds pipelines that extract, normalize, validate, and link information from clinical documents and publications into Aurora and GraphDB. Develops embeddings, vector search, RAG workflows, data-serving APIs, lineage tracking, and regulatory audit trails. The role also requires AWS-based orchestration, clinical data quality controls, biomedical knowledge graph modeling, and deployment automation using infrastructure-as-code and containerization.