Top Remote Analysis Reporting Jobs in Sacramento, CA

The VP, Head of Policy & Data Operations manages data governance and operations for proxy voting policies, ensuring data integrity and operational excellence while collaborating across teams to optimize processes and manage risks.

Execute day-to-day pricing analytics: prepare and clean retail pricing and promo data, run and validate pricing models and agent outputs, monitor in-season performance, assemble clear analytical reports for business reviews, and contribute to improving pricing agents and documentation to scale the pricing function.

Build and maintain large-scale data processing pipelines using Apache Spark (PySpark/Scala) and Python. Design ETL workflows, implement distributed data processing, use version control (Git), and work with cloud platforms (GCP/AWS/Azure).

Manage travel demand modeling projects, oversee deliverables, mentor staff, and develop innovative forecasting solutions for multimodal transportation systems.

Design and maintain scalable dbt data models and Looker dashboards; partner with Finance, Product, and GTM to translate requirements into analytics solutions; ensure data quality with Data Engineering; perform analyses, forecasting, and QA to deliver trusted reporting and drive analytics initiatives.

Lead client-facing Data & Analytics engagements across pre-sales, architecture, and delivery. Define strategy, roadmaps, solution designs, and SOWs for modern data platforms, pipelines, governance, analytics, and AI enablement. Drive practice development, create reusable IP, mentor teams, and ensure quality delivery and strong business outcomes.

Design, build, and maintain dbt data models and scalable ELT pipelines; optimize performance-aware SQL on Snowflake; ensure observability, testing, and CI/CD; partner with product and engineering teams to meet analytic needs, mentor engineers, document business logic, and troubleshoot ingestion, transformation, and warehouse issues.

As a Sr. Staff Deployment Strategist, you will drive business transformation by partnering with clients to design and implement AI-powered data intelligence solutions, ensuring value realization and client integration.

Support a Department of State data engineering program: review data policies and governance, define requirements, build and maintain Palantir-based data pipelines, clean and integrate datasets, detect and remediate data fidelity and pipeline issues, produce analyses and visualizations, and coordinate with non-technical users and stakeholders.

Drive enterprise automation by identifying workflow inefficiencies across Home Health, Primary Care, and Pharmacy. Use data analysis, process and journey mapping, and MDM to define opportunities and leading indicators. Partner with product, engineering, clinical, compliance, and operations to design, validate, and scale AI-enabled automation solutions that improve outcomes and efficiency while ensuring regulatory compliance.