Top Data & Analytics Jobs in Ann Arbor, MI

This role involves leading data infrastructure modernization efforts, architecture reviews, and migration planning while providing technical mentorship and establishing operational standards.

Lead design and development of web UI and REST middleware within an Agile team. Define requirements and acceptance criteria, implement Java/Spring and Angular solutions, build CI/CD pipelines, work with Product Owner and testers, and produce/update design documentation.

The Senior Data Engineer will maintain and improve data infrastructure, design ETL processes, and create high-performance pipelines for analytics and AI initiatives using SQL and Python in cloud environments.

Perform part-time quality audits and evaluations of task outputs, define and refine quality benchmarks and scoring rubrics, analyze audit results to produce actionable insights and reports, and recommend process improvements to raise output quality.

Lead architecture and execution of Grafana's marketing data stack and analytics practice. Build forecasting, predictive, and causal models, design BigQuery schemas, deploy agentic AI and automated pipelines, partner with GTM leadership, and deliver executive-grade insights to drive demand generation and ROI.

Facilitate one-time transfers of customer data into Encompass Cloud Platform. Plan migrations with stakeholders, extract and transform legacy data using ETL/ELT methods, import and validate data, resolve issues, and execute migration activities on schedule to support customer onboarding and go-live.

Restructure and maintain Airtable relational architecture for fertility industry data, implement automations and integrations (Zapier, Softr), enforce data governance and permissions, build dashboards and reports, execute data acquisition and enrichment to scale the database, conduct audits, document SOPs, and support onboarding and system monitoring.

Design and deliver Databricks-centric data architectures, lead pre-sales and billable engagements, build end-to-end data engineering pipelines for AI/ML and BI, mentor teams, ensure data governance/security/quality, and resolve data system issues while producing solution documentation and presentations.

Design, build and maintain scalable, auditable analytics-ready data models (primarily in dbt) for PBM and care navigation. Implement data quality checks, CI/CD, documentation, pipeline orchestration, and partner with stakeholders to enable self-service analytics and AI-enabled workflows.

Lead design and evolution of a cloud-native Snowflake data platform using medallion/lakehouse patterns. Implement governance, security, ingestion integrations, cost forecasting, and observability. Collaborate with Azure teams, mentor engineers, and translate architectural trade-offs for stakeholders while championing AI adoption.