Top Data & Analytics Jobs in Ann Arbor, MI

Owns the enterprise Snowflake data platform end to end, including architecture, ingestion, transformation, security, governance, reliability, performance, cost optimization, and AI enablement. Establishes engineering standards, reviews architecture, resolves complex production issues, mentors data professionals, and leads cross-functional adoption of scalable, governed analytics capabilities. The role provides senior technical influence without direct people management and supports secure MCP-based AI integrations.

Supports ADL’s Center on Extremism law enforcement and audit teams by maintaining a law enforcement database, preparing reports, reviewing incidents, cleaning data, and analyzing trends. The intern will help improve data quality, inform research and reporting, collaborate with subject matter experts, and present work internally.

Own analytics for Root’s Customer Experience domain and policyholder retention. Develop metrics, analytical frameworks, experimentation systems, and strategic recommendations. Partner cross-functionally with Product, Engineering, Data Science, and Operations to shape roadmaps, evaluate customer initiatives, quantify business impact, and influence senior leadership decisions through rigorous analysis and clear communication.

Leads and manages an analytics engineering team while contributing to data transformation, modeling, quality, and delivery solutions. Establishes modeling and development standards, implements analytics engineering tools, supports client engagements, improves reporting and visualization processes, allocates team resources, mentors engineers, supports presales, and drives internal quality and process improvements.

Analyzes business and operational needs, gathers requirements, evaluates data and systems, and recommends technology solutions. Develops advanced SQL queries, reports, system models, and process improvements. Responsibilities include troubleshooting, data architecture integration, software and hardware solution design, database analysis, automation using scheduling or RPA tools, and project leadership. Senior levels guide other analysts and assess technology’s business impact.

Design and implement enterprise data architectures supporting batch and real-time analytics, ETL/ELT, data warehouses, streaming pipelines, CDC, and cloud data platforms. Build AI-ready data infrastructure for RAG, vector search, and Generative AI applications. The role requires production experience with Treasure Data/CDP, Kafka, Snowflake or Databricks, cloud services, and modern AI data engineering technologies.

Owns MCA’s Azure data warehouse architecture, ETL pipelines, semantic models, reporting infrastructure, system integrations, and internal Azure applications. Designs and monitors integrations among NetSuite, HubSpot, and other systems; develops automation and tools; maintains security, documentation, testing, and deployment processes. The role also leads adoption of AI-assisted development practices, validates AI-generated code, and collaborates across Data Warehouse and Business Systems teams.

Manages the customer care call quality monitoring program across multiple teams. Maintains quality standards, scoring configurations, dashboards, and reporting; analyzes contact trends and customer insights; partners with managers to improve coaching and performance; administers the quality management platform; develops training and support materials; and collaborates with customer experience and technology teams to improve customer interactions.

Owns analytical projects across customer onboarding, transaction behavior, and platform operations. Designs dashboards, KPI frameworks, reporting workflows, and data pipelines while delivering actionable insights. Partners with Engineering, Product, Payment Operations, Compliance, and Finance; mentors colleagues; manages project scope and priorities; resolves ambiguity; and drives cross-functional alignment. Requires advanced SQL and data modeling skills, BI tool experience, analytical scripting familiarity, FinTech domain knowledge, and 4+ years of analytics experience.

Lead analytics partner to Community Support, driving data-driven roadmaps, scalable reporting and measurement, causal inference and experimentation, and improvements to agent/guest/host experiences via analytics, modeling, and stakeholder influence.