Top Analysis Reporting Jobs in Detroit, MI

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.

Own and maintain Center of Excellence network reporting and health metrics. Build recurring and ad hoc dashboards using Databricks, Python, and SQL. Conduct network adequacy and coverage analysis, validate and distribute reports, surface risks and trends, support client meetings, and produce executive-ready summaries while documenting processes and standards.

Lead reporting and analysis across product, call center, and marketing; manage enrollment and revenue reconciliation; produce partner and carrier reports; analyze member engagement and plan performance to surface actionable insights.

Design, develop, maintain, and optimize ADABAS database structures and data solutions. Support mainframe data processing (Natural, COBOL, JCL), perform migrations to modern platforms, tune performance, ensure data integrity/security, troubleshoot issues, and collaborate with developers, architects, and analysts on modernization, API/cloud integration, and data warehousing initiatives.

Lead end-to-end FOIA data migration projects into RelativityOne, define and prioritize migration tooling, author requirements and runbooks, engage agency customers, ensure FedRAMP-compliant handling of DT1 data, and drive continuous improvement and product feedback.

Build and maintain Power BI reporting products, integrate and validate institutional data, conduct applied quantitative and qualitative research, deliver analyses and visualizations, manage projects and reporting standards, and support cross-organization analytics and stakeholder decision-making.

Investigate financial transactions to identify potential money laundering activities, utilize AI for analysis, document findings, and collaborate with product teams on improvements.

As a Senior Data Analyst, you will analyze game telemetry data, translate business needs into insights, and guide technical teams. You will also lead exploratory data analysis and maintain data quality practices.

Design, build, and maintain scalable, secure data architectures, models, and ETL pipelines. Integrate diverse data sources, optimize performance and data quality, implement governance, monitor production SLAs, and collaborate with data scientists, analysts, and product teams. Provide technical leadership, documentation, and training to improve engineering practices across the organization.

Lead development of cloud data platforms and end-to-end data pipelines using AWS/Snowflake and big-data technologies (Spark, Hive, Iceberg). Automate builds and deployments with Bash/Python shell scripting, apply CI/CD and Medallion Architecture, perform data modeling and warehousing, and collaborate across teams. Pharma/AbbVie experience preferred.