Top Senior Data & Analytics Jobs in Ann Arbor, MI

Design, build, tune, and maintain Oracle-based data warehouse solutions and ETL processes. Develop PL/SQL, SQL, SSIS packages, and Unix scripts; manage jobs, scheduling, and monitoring; perform performance tuning, debugging, and production support; collaborate with DBAs, analysts, and teams to implement and document robust data solutions while meeting SLAs.

Design, build, and maintain scalable batch and streaming data pipelines and analytics-ready data models. Implement cloud (primarily AWS) data platform solutions, data ingestion, transformation, orchestration, and observability. Embed data quality, governance, security, and metadata/lineage practices. Partner with architecture, analytics, and application teams to enable self-service analytics, reporting, and downstream use cases while driving platform evolution and engineering best practices (CI/CD, testing, documentation).

Design, build, and maintain scalable, fault-tolerant streaming data architectures and real-time pipelines using Kafka, MSK, and Kinesis. Implement stream processing, monitoring, security, IaC, and CI/CD. Collaborate with data teams, provide technical leadership, and optimize latency, throughput, and cost for real-time analytics and downstream systems.

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.

Lead data engineering for a healthcare scheduling platform rebuild: map legacy multi-TB schema, design target schema, build translation layer (views/materialized views and write mappers), ensure data consistency during parallel systems, plan per-tenant cutover with verification and rollback, tune DB performance, instrument data quality/lineage/audit, and mentor engineers.

Lead a team to analyze sales data, build and maintain Power BI and Excel reporting, leverage AI and automation for pipeline and lead scoring, align cross-functional GTM strategies, ensure data quality, and deliver actionable, executive-ready insights to drive sales performance and quota attainment.

Lead strategy-science initiatives for credit and fraud across acquisition and account management. Use advanced analytics, experimentation, and ML to identify opportunities, design solutions, and deliver executive recommendations. Partner with cross-functional teams to implement scalable decisioning, mentor junior staff, and measure impact while balancing customer experience and regulatory constraints.

Lead healthcare data analysis and quality efforts across claims, pharmacy, and enrollment data. Translate business needs into technical requirements, build complex queries, recommend process and data improvements, manage projects, and mentor team members while liaising between operations, R&D, and IT.

Lead design and delivery of end-to-end BI solutions and market-facing analytics tools. Define strategy and roadmaps, translate business needs into requirements, guide development and testing, oversee deployments, ensure data governance, and liaise with stakeholders to prioritize fixes and maintain documentation and compliance.

Lead BI Developer owns reporting infrastructure end-to-end, building standardized, trusted dashboards and LookML models, analyzing messy third-party data, partnering with Yield/Paid Media/Account teams to deliver actionable performance marketing insights and retrospective analyses that drive business decisions.

Lead BI developer who owns reporting infrastructure end-to-end: SQL-based data extraction from messy sources, LookML/BI model development, dashboard standardization, stakeholder partnership, and performance marketing optimization to drive actionable insights and business outcomes.

Lead ownership of BI reporting infrastructure: build and standardize dashboards, extract insights from messy third‑party data, partner with marketing teams to drive performance optimization and deliver proactive retrospective analyses that influence business decisions.