Top Senior Analysis Reporting Jobs in Sacramento, CA

The position involves leading database operations and managing data integration for business intelligence, focusing on PostgreSQL and ETL/ELT pipelines.

The Director of Cloud FinOps will manage financial operations related to public cloud, optimize costs, and partner with various teams to maintain efficiency and profitability.

The Senior Clinical Trials IT Business Analyst bridges Clinical Development and IT, optimizing clinical trial technologies and managing system implementations, validations, and stakeholder engagement.

As a Senior Data Engineer, you will enhance the data lakehouse, optimize data workloads, perform complex transformations, and develop frameworks to improve delivery velocity, focusing on cybersecurity solutions.

The role involves managing actuarial modeling for Retirement Plans, ensuring quality of outputs, overseeing BAU execution, and training junior staff.

Analyze revenue and growth performance, provide insights on auction behavior, measure A/B tests, define KPIs, and perform root-cause analysis.

Lead global partner analytics and planning for partner GTM motions. Build dashboards, business models, AI-enabled workflows, and executive reports to support partner planning, incentives, coverage, performance management, and cross-functional decision-making across hyperscalers, ISVs, marketplaces, and reseller channels.

Lead data-focused business analysis: elicit and document requirements, model data and processes (As-Is/To-Be), design data flows, support integrations, migrations, EDW/reporting decisions, mentor team members, and drive data governance and cataloguing across enterprise systems.

Design, build, and scale reliable batch and real-time data pipelines and warehouses. Partner with engineering, data science, and business teams to define data models, improve observability, optimize storage and querying, and evangelize data engineering best practices across the company.

Lead data engineering for a healthcare scheduling platform rebuild: map legacy multi-TB schema, design target schema, build translation layer (views/materialized views and write mappers), ensure data consistency during parallel systems, plan per-tenant cutover with verification and rollback, tune DB performance, instrument data quality/lineage/audit, and mentor engineers.