Top Data & Analytics Jobs in Ann Arbor, MI

Build and maintain enterprise data pipelines and infrastructure supporting natural-language querying, semantic search, knowledge graphs, and GraphRAG for the SEC. Responsibilities include onboarding data sources, processing XBRL and financial filing data, managing metadata and lineage, validating data quality, monitoring pipeline health, resolving integration issues, and using AWS data services. The role also requires compliance with federal security standards and collaboration with the Data Architect.

Develop and maintain reports, dashboards, and business intelligence solutions to support decision-making. Consult with stakeholders, document business processes, administer business tools and systems, troubleshoot issues, and support solution implementation. Identify process-improvement and automation opportunities, manage change documentation, and respond to ad hoc data requests while collaborating across teams.

Build and operate large-scale data pipelines, web-scraping systems, and data-collection tools for AI datasets. Maintain analytical databases, optimize queries, troubleshoot pipeline and data-quality issues, manage containerized workloads across Kubernetes and Linux infrastructure, and support CI/CD workflows. The role also involves documenting technical processes, researching improvements, and developing scalable APIs in a fully remote environment.

Designs, develops, and maintains data pipelines, ETL processes, integrations, data infrastructure, and complex data models. Supports analytics teams by sourcing and transforming business data for reporting and AI tools. Responsibilities include requirements gathering, development, testing, deployment, production support, SQL performance tuning, troubleshooting, stakeholder communication, and mentoring. The role also delivers data warehouse projects and builds scalable solutions across diverse data sources and cloud-based platforms.

Gather and clarify business requirements; translate needs into user stories, acceptance criteria, workflows, and business rules. Collaborate with product, engineering, data, and QA teams throughout development. Analyze processes and operational data, support backlog refinement, validate delivered functionality, and track dependencies and requirement changes. Participate in stakeholder discovery and project discussions while helping ensure analytics platform solutions address business needs.

Maintain operational and product data quality by processing records, performing validation checks, investigating discrepancies, supporting imports and updates, monitoring workflows, preparing routine reports, documenting procedures, and coordinating issue resolution with Data, Product, Engineering, and Operations teams. The role also supports testing data-process changes and improving accuracy and consistency in a remote environment.

Prepare and maintain recurring business and operational reports, dashboards, and spreadsheets. Collect, validate, and analyze data, investigate discrepancies, monitor reporting accuracy, and translate business questions into reporting requirements. Document processes and data sources, support ad hoc analysis, present findings clearly, and collaborate with Data, Product, Engineering, and Operations teams to resolve issues and improve reporting automation.

Conducts public health data validation, management, quality assurance, geospatial and molecular HIV analysis using SAS and R. Responsibilities include developing codebooks and data management plans, identifying discrepancies, performing duplicate and comparison procedures, generating reports, interpreting results, disseminating data, and collaborating with analysts, federal partners, jurisdictions, and community-based organizations.

Develops SAS and R programs to validate, clean, analyze, and document public health surveillance and research datasets. Responsibilities include data quality checks, discrepancy identification, codebook and data management plan creation, duplicate and results comparison procedures, geospatial and molecular HIV analysis, reporting, and data dissemination. Collaborates with analysts and federal partners supporting CDC HIV prevention programs and funded jurisdictions.

Develops and supports claims-related data pipelines, curated datasets, reporting layers, dashboards, and analytics assets. Partners with stakeholders to research data, clarify ambiguous requests, and design scalable solutions. Writes complex SQL, builds Power BI reports, and develops Databricks pipelines, transformations, workflows, and automation. Supports migration to Databricks and contributes to AI/ML and generative AI initiatives involving healthcare data.

The Senior Data Analyst/Informaticist analyzes complex data, develops predictive and AI-enabled models, forecasts behavior, optimizes programs, and translates findings into recommendations for senior leadership. The role coordinates with analytics, IT, business teams, and subject matter experts; validates analytical solutions; improves operational and financial outcomes; and supports strategic decision-making through data-driven insights and automation.

Build, test, maintain, and enhance Workday financial reports, dashboards, and reporting solutions. Gather requirements, validate and reconcile data, document report logic, troubleshoot performance issues, support Workday implementations and releases, and train end users. Partner with Finance, HR, Supply Chain, and other stakeholders to ensure accurate, compliant, and actionable reporting across a nonprofit healthcare system.

Leads the design and delivery of scalable data pipelines, dbt models, orchestration workflows, and analytical data models. Establishes data architecture, engineering standards, quality frameworks, governance, observability, and self-service analytics practices. Partners with stakeholders, leads technical reviews, mentors engineers, supports hiring, oversees analyses, and participates in incident response and continuous improvement.

Lead reporting and application-integration architecture across Power BI, PBIRS, Power BI Embedded, and Crystal Reports. Build and optimize paginated reports, SQL queries, and stored procedures; troubleshoot app-to-report integrations; support Python data tooling; automate report delivery; implement monitoring, quality checks, anomaly detection, SLAs, and performance benchmarking.