Top Analysis Reporting Jobs in Sacramento, CA

As a Data Scientist, you will analyze blockchain data to derive insights, develop and deploy predictive models, and improve product offerings.

As a Senior Forward Deployed Data Engineer, you will design and implement data pipelines for media agency clients, manage technical delivery, and ensure data security while mentoring junior engineers and communicating effectively with stakeholders.

As a Credit Risk Senior Analyst at Marqeta, you'll lead underwriting strategies, refine credit policies, conduct risk analyses, and present findings to senior management.

Lead the architectural direction of Seer's data platform, mentor engineers, optimize data processes, and integrate AI solutions to enhance data-driven decision-making.

Design, build, and operate production-grade data ingestion pipelines and dbt transformations into a Databricks lakehouse. Establish data quality, monitoring, and observability. Partner with Product and Engineering to enable metrics, dashboards, and longitudinal patient analytics supporting clinical and operational decision-making.

The Staff Data Engineer will enhance the data ecosystem at WeightWatchers by developing data pipelines, collaborating cross-functionally, and ensuring data quality while leading projects and technical initiatives.

The Data & Analytics team at Surescripts transforms healthcare data into actionable insights, collaborating with various stakeholders to support critical decisions across the healthcare ecosystem.

Entefy seeks a Senior Data Scientist with a Master's or PhD in a relevant field, and 3+ years of experience. Responsibilities include delivering advanced analytics, leading teams, and extracting insights from datasets.

The Sr. Data Engineer - Databricks designs and maintains scalable data solutions using Apache Spark and Databricks, ensuring data quality and performance for analytics and reporting.

Design, implement, and support enterprise data integrations connecting JDE, Workday, Salesforce and other platforms. Lead SQL-driven ETL/ELT pipelines, develop reusable integration frameworks, ensure data integrity and audit readiness, perform regression and production troubleshooting, and provide architectural oversight and mentorship across multiple concurrent projects.