Top Analysis Reporting Jobs in Ann Arbor, MI

As a Data Engineer, you will develop solutions for customer-centric technology, ensuring platform integration and managing data architecture. Responsibilities include building data processes, maintaining data integrity, and collaborating cross-functionally to meet business challenges.

The Business Intelligence Analyst will analyze pharmaceutical transaction data, develop visual data models, and collaborate cross-functionally to drive insights and improvements in business strategies.

As a Senior Analytics Engineer, you'll build data pipelines and dashboards, partner with stakeholders for KPI development, and ensure data quality across the company.

The Data Engineer will design and maintain scalable data pipelines, automate workflows, and enhance data governance while collaborating with cross-functional teams.

The Data Migration Specialist will ensure successful data transitions from legacy systems, engage in ETL processes, and provide customer support throughout the migration journey.

The Director of Data Analytics & Business Intelligence leads analytics functions, building models and dashboards while guiding a team. Responsibilities include analytics infrastructure management, cross-functional collaboration, and driving AI/ML initiatives.

The Senior Data Engineer will design and implement complex data models, collaborate on data governance, lead data initiatives, and mentor team members.

Design, build, and maintain Scala-based ETL and streaming data pipelines, APIs, and data microservices in Azure. Optimize LLM fine-tuning and RAG workflows, support DevOps/CI-CD practices, document standards, mentor engineers, and manage data ingestion frameworks for analytics and partner integrations.

Support national community lending initiatives by developing ROI dashboards, analyzing event and CRM data, coordinating events and partners, enabling sales teams, managing budgets/contracts, and producing program performance insights to scale community outreach and homeownership programs.

Partner with Product, Design, Engineering, and Data to define KPIs and measurement for AI-powered features, guide instrumentation, design and evaluate experiments, build dbt models, create dashboards, and influence product analytics standards and long-term strategy.