Top Analysis Reporting Jobs in Detroit, MI

Lead design and implementation of scalable data architectures in Azure/Databricks/Fabric, enhance governance (Unity Catalog), improve data quality frameworks, build resilient ingestion/transformation pipelines, modernize CI/CD and source control, support production and analytics/AI use cases, and collaborate with stakeholders to move proofs-of-concept to enterprise solutions.

Lead the Master Data Management upgrade project from version 10.1 to 11.4, ensuring effective implementation and system integration.

Partner with teams to design reporting, automation, and AI-enabled solutions. Build Power BI dashboards and data models, prepare and validate data with Excel/SQL/Power Query, create low-code workflows (Power Automate), maintain SharePoint/Microsoft 365 solutions, and promote responsible use of AI to streamline processes and improve decision-making.

Design, build, and maintain scalable Databricks-based ETL/ELT pipelines (batch and streaming) using Spark, Delta Lake, DBT, PySpark/SQL. Support MLOps with MLflow, build CI/CD, monitor pipelines and models, ensure data quality/security, optimize Databricks resources, integrate with cloud platforms, and mentor junior engineers.

The Business Objects Architect will manage the administration, governance, and architecture of Business Objects solutions, ensuring standards are maintained and coordinating upgrades.

Analyze large healthcare datasets, build and implement quantitative models, perform statistical analyses, ensure data accuracy, collaborate with cross-functional teams, and provide actionable insights to improve healthcare delivery.

Leads College Board’s Operations analytics strategy and team, developing forecasting, predictive modeling, optimization, cost assessment, and decision-support capabilities. Partners with senior leaders across Operations, Product, Program, Technology, and Finance to improve execution, customer experience, efficiency, and cost savings. Responsibilities include setting technical direction, embedding analytics into operational decisions, presenting insights, hiring and coaching analytics staff, and building future AI and data-infrastructure capabilities.

Develop and maintain data ingestion pipelines, relational databases, ETL/ELT workflows, cloud resources, data reliability monitoring, and AI-enhanced applications. Integrate LLM APIs and MCP connectors, write Python and R automation code, migrate siloed processes into centralized systems, and collaborate with technical and non-technical stakeholders. The role also supports Azure deployments, enterprise data integrations, dashboards, reporting, and cloud data security.

Leads data engineering teams responsible for secure, scalable, governed data platforms and pipelines. Oversees Snowflake architecture, performance, security, cost optimization, data quality, governance, access controls, metadata, lineage, and audit readiness. Manages budgets, staffing, engineering standards, platform reliability, and continuous improvement while partnering with product, analytics, AI, security, compliance, infrastructure, vendors, and auditors. Develops managers and builds high-performing data engineering organizations.

Own healthcare analytics data methodology, including episode grouping, provider attribution, cost standardization, quality measures, reference data, pipelines, QA, and production delivery. Translate feature requests into specifications and validated analytics. Reconcile results, establish recurring data-quality coverage, investigate failures, and collaborate with engineering, data science, product, clinical informatics, and customer teams. Advanced SQL and healthcare claims expertise are central to ensuring accurate, defensible customer metrics.