Top Data & Analytics Jobs in Detroit, MI

Build and maintain production-grade data pipelines and ELT processes using Python, SQL, Airflow, and dbt within AWS. Design optimized schemas in PostgreSQL and Redshift, leverage AI/LLMs to improve development, automation, testing, and data quality, and scale infrastructure for large healthcare datasets.

Lead growth analytics for acquisition and activation funnels: measure channel performance, build data models and KPI reporting, run experiment analysis, and translate insights into business recommendations. Partner with Growth product team and leadership to visualize results and drive strategy.

Lead architecture, implementation, and optimization of scalable data platforms, ETL/ELT pipelines, and data governance. Ensure security and compliance, mentor junior engineers, drive CI/CD and IaC for data workflows, and collaborate with stakeholders to deliver actionable analytics and reporting.

Lead enterprise sales forecasting, pipeline governance, and KPI reporting to drive growth performance. Own forecast reviews, executive reporting, sales compensation tracking, and data-driven insights. Partner cross-functionally with Sales, Finance, Growth Ops, and Market Leaders to improve conversion, planning accuracy, and revenue outcomes, while supporting systems, data quality, analytics automation, and performance frameworks.

Design and recommend Snowflake-based analytic architectures, lead implementation work streams, advise engineering teams on data cloud migrations, mentor junior staff, support presales, and leverage AI to optimize data warehouse and lake solutions across project lifecycles.

Design, build, and maintain scalable distributed data pipelines and a secure data lakehouse for streaming and batch processing to support real-time analytics, ML, and experimentation. Automate, test, and harden workflows, architect logical and physical data models, build ML model features, and collaborate with product, analytics, and data science teams to turn data into value.

Build and operate ingestion and transformation pipelines, model and test core warehouse data, enable analytics and reporting, and maintain ML data infrastructure feeding matching and recommendation models. Partner with Engineering, Product, and Data Science to ensure reliable, documented, and trusted data at scale.

The Solutions Analyst delivers reporting and operational outputs, analyzes datasets, resolves issues, maintains solution components, and collaborates with teams to improve efficiency.

Design and own capital and catastrophe modeling frameworks to evaluate policy- and portfolio-level risk and capital. Run and integrate catastrophe model outputs, build analytical tools and data structures, assess reinsurance impacts, and translate results into actionable recommendations for underwriting, finance, and portfolio strategy.

Lead and grow a data engineering team to design, build, and operate scalable, cost-efficient data lakehouse pipelines and infrastructure. Define technical strategy, enforce engineering best practices (CI/CD, testing, monitoring), own roadmap and capacity planning, collaborate with product and engineering stakeholders, manage on-call and operational automation, and hire talent. Ensure data governance, lineage, and compliance in a regulated healthcare environment.