Top Data & Analytics Jobs in Ann Arbor, MI

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.

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.

Support research and analysis of social and environmental impact for investments, focusing on climate risk and greenhouse gas management. Conduct market and company research, synthesize findings, prepare analyses and presentation materials, and support deal teams and portfolio engagement on responsible investing and sustainability topics.

Build dashboards and reports tracking enrollment, attendance, engagement, and attrition. Develop predictive models to identify at-risk students, analyze withdrawal causes, monitor early-warning indicators, partner with cross-functional teams to design retention interventions, and present insights to leadership while supporting data pipeline accuracy.

Lead enterprise data strategy and governance to establish semantic architecture, metadata, lineage, stewardship, and standards enabling trusted data for AI, analytics, and operations. Define operating model, policies, reference architectures, and roadmaps while partnering with Legal, Compliance, Security, Technology, and business leaders to ensure regulatory compliance and enterprise-wide adoption.

Own end-to-end client data migrations: reverse-engineer legacy ETL, design and build Airflow DAGs and Spark jobs, validate and reconcile data at scale, document architecture and decisions, and coordinate cross-functional teams through go-live and hypercare.

The Senior Data Engineer will develop data engineering solutions, manage ETL workflows, and establish a new data practice while collaborating with stakeholders.

Design and run evaluation frameworks to assess third-party vendor data for fraud detection. Build lift analyses, backtests, and champion/challenger tests; profile vendor datasets for quality and coverage; collaborate with fraud, product, and data engineering to define ingestion and testing requirements; translate findings into actionable recommendations and maintain an internal knowledge base; support ad hoc analyses on fraud trends and model performance.