Top Data & Analytics Jobs in Sacramento, CA

Analyze and reverse-engineer legacy tax data for conversion into TaxSys. Create data mapping specifications for developers, QA conversion results, investigate data issues, prepare data for customer training and verification, and guide clients through conversion decisions and go-live. The role also involves customer communication, project documentation, planning, time management, and potential project leadership.

Early-career Data Engineering Analyst supporting AIG’s Data Office through a rotational program. Responsibilities include developing cloud-based data pipelines, collecting and transforming data, building modern software systems, and supporting analytics and data science use cases. The role emphasizes data quality, security, compliance, collaboration, analytical problem-solving, and professional development through mentoring, masterclasses, and on-the-job experiences.

Build and support enterprise data lakes, lakehouses, ETL/ELT pipelines, streaming platforms, and business intelligence solutions. Responsibilities include processing large-scale data, implementing data quality, governance, metadata, lineage, monitoring, anomaly detection, and observability frameworks, and supporting production Linux-based distributed data platforms. The role also provides technical leadership, mentorship, code and design reviews, performance optimization, and support for secure handling of sensitive information.

Own data ingestion, transformation, exchange, and integration workflows between K–12 Student Information Systems and Timely’s scheduling platform. Ensure pipeline accuracy, security, reliability, and scalability while collaborating with engineering, product, customer success, district IT teams, and SIS vendors. Develop documentation, process improvements, automation scripts, and lightweight Python tools; lead discovery for new SIS integrations and help scale the data integrations function.

Analyze business performance, develop hypotheses, answer critical business questions, and build dashboards and reports in Sigma. Support budgeting, forecasting, data quality checks, and reconciliations while partnering with teams across growth, product, insurance, finance, and leadership. Serve as a trusted data advisor by answering metric and reporting questions and promoting data-driven decision-making.

Own go-to-market funnel reporting, dashboards, data quality, and analysis for Sales, Marketing, and RevOps. Integrate CRM and marketing data, monitor lead scoring and attribution models, investigate funnel performance, identify root causes, and provide actionable recommendations. Maintain reporting systems, audit data hygiene and tool adoption, and communicate insights clearly to non-technical stakeholders in a remote-first SaaS environment.

Own experimentation analytics across Product and Marketing, including A/B and multivariate test design, causal inference, statistical analysis, and business recommendations. Build dbt models, dashboards, metrics, and experimentation frameworks; improve data infrastructure and self-service reporting; partner with engineering on instrumentation; mentor analysts; and maintain the analytics roadmap while supporting cross-functional stakeholders.

Design and build a durable data storage platform that preserves source disagreements, provenance, uncertainty, historical versions, and evidence. Develop result and evidence stores, lineage tracking, versioned rules and configurations, reproducible decision records, and point-in-time entity views. Collaborate with entity-resolution and machine-learning teams to support probabilistic outputs. The role requires production data engineering experience, strong Python and SQL, PostgreSQL expertise, U.S. citizenship, and an active Secret clearance.

Supports client projects by creating metadata, writing and testing R syntax, cleaning and recoding survey data, performing statistical operations, reviewing code and outputs, documenting data-management processes, and troubleshooting errors. The role requires independent task management, technical communication, quality control, and collaboration on federally contracted projects involving sensitive information.

Develop marketing budget allocation models, Early LTV metrics, performance diagnostic frameworks, and analytical tools. Analyze products, channels, campaigns, cohorts, attribution, and marketing economics using SQL, experimentation, BI tools, and spreadsheets. Support AI-based analytics development and unified BI metrics while translating findings into business rules and recommendations.