Top Senior Analysis Reporting Jobs in Sacramento, CA

Design and deliver end-to-end Azure Data & AI solutions. Lead technical presales, architect production-ready lakehouse platforms, guide delivery teams, ensure CI/CD, governance, performance, cost optimization, and strong client satisfaction.

The Manager of Solutions Engineering will lead a team of Solutions Engineers, focusing on customer engagement, technical demonstrations, and mentoring while enhancing POC success.

The Data Analyst will support operational reporting and stakeholder needs, working with SQL and Artiva to meet business requirements through data and reporting solutions.

The Solutions Consultant will conduct product demos, assist in sales cycles, and provide evidence of product value while maintaining product knowledge and client relations.

The Senior Business Systems Analyst analyzes and optimizes systems, gathers requirements, collaborates with stakeholders, implements technology solutions, and manages change to improve efficiency.

Lead a small BI team while remaining hands-on: write advanced SQL, build dashboards and models, enable self-service analytics, set governance, surface insights for stakeholders, and shape a BI roadmap that scales with alerting, anomaly detection, and applied AI/ML.

The Product Analyst will measure results and deliver insights on new AI products, identify opportunities, and guide product strategy through data analysis and visualization.

The Senior Consultant will lead the design and implementation of data solutions using Microsoft Fabric, Power BI, and Databricks to enhance analytics capabilities for clients. They will engage with stakeholders to define data strategies and deliver high-quality consulting services across multiple projects.

The Senior Bioinformatics Data Engineer will build data pipelines, implement clinical data ingestion, and optimize platform infrastructure while ensuring data quality and compliance with legal standards.

Lead and build Newfire's clinical data engineering practice: define architectures, reusable patterns, and governance; own analytics and transactional pipelines; provide hands-on technical leadership with Databricks/Snowflake/dbt; mentor and grow the team; partner commercially to identify opportunities; and integrate practical AI capabilities for healthcare data use cases.