Top Senior Data & Analytics Jobs in Ann Arbor, MI

Lead design and delivery of a scalable, multi-product data platform. Architect and build robust batch and streaming pipelines, modernize legacy systems, improve observability, and partner with product, data science, and engineering to enable AI-driven solutions at scale.

Lead and build Newfire's clinical data engineering practice: define architectures, reusable patterns, and governance; own analytics and transactional pipelines; provide hands-on technical leadership with Databricks/Snowflake/dbt; mentor and grow the team; partner commercially to identify opportunities; and integrate practical AI capabilities for healthcare data use cases.

Lead design, build, and optimize scalable ETL/ELT data pipelines and analytics platforms using Databricks and Spark. Integrate and transform source data into analytics-ready layers, maintain data documentation and lineage, optimize SQL Server performance, collaborate with product and engineering teams, and apply AI-enabled tools responsibly to drive business insights.

Lead business intelligence efforts to analyze complex data, define KPIs, identify operational inefficiencies, and recommend process improvements. Collaborate with cross-functional teams and executives to implement data-driven strategies, manage improvement projects, monitor resource allocation, and ensure compliance with policies and regulations.

Own Mixpanel and partner closely with Product to turn product-level data into decision-grade insights. Define instrumentation and event taxonomy, build dashboards and notebooks, run cohort and retention analyses, design and analyze A/B tests, and collaborate with data engineers to model product event data. Document metrics, maintain a living glossary, and translate findings into actionable product recommendations.

The Senior Azure Data Consultant will build and maintain data pipelines, develop lakehouse solutions, optimize ETL processes, and support analytics capabilities in a Microsoft Fabric environment.

Lead data engineering strategy and design scalable data ecosystems. Build and maintain distributed ETL pipelines, enforce data governance (PII/PHI), improve developer efficiency, mentor engineers, and align technical work to business objectives while delivering reliable, monitored production systems.

Design, build, and maintain data integration, warehouse, and BI solutions supporting subscriber acquisition, campaign and storefront systems. Create schemas, stored procedures, dashboards, and reports; optimize queries; aggregate multi-source data; ensure data quality, PII compliance, and platform observability. Collaborate across teams, mentor engineers, and provide executive reporting and analytics for video/OTT products.

Lead analytics strategy for client accounts: create measurement plans, testing roadmaps, and cross-channel analyses. Use BI tools and SQL to connect data, generate insights, and present clear, actionable recommendations to clients and internal teams.

Design, build, and maintain scalable Databricks-based data pipelines and ELT workflows; develop and document dbt models; define data modeling methodology; ensure data quality, reliability, and scalability; collaborate with clients and cross-functional teams; provide technical guidance and deliver improvements to clients' data infrastructure and analytics capabilities.