Top Data & Analytics Jobs in Detroit, MI

Develop data models and automated solutions supporting semiconductor supply chain mapping, resiliency, distribution operations, and supply forecasting. Perform exploratory and targeted analyses, preprocess structured data, monitor model effectiveness, and present insights through data visualization. Collaborate with technical teams and stakeholders on cross-functional projects, communicate data-driven recommendations, and manage ambiguous business problems independently. The role requires domestic and international travel of less than 25% and follows a hybrid work schedule.

Designs, develops, and maintains data platforms, pipelines, and integration solutions across on-premises and cloud environments. Responsibilities include resolving data quality and security issues, building ELT processes, developing data scripts and relational or non-relational models, and monitoring data lake performance and scalability. The role also supports analytical and operational decision-making through reliable data solutions and collaborates with cross-functional teams.

Analyze complex datasets, develop data models, dashboards, and visualizations, and conduct predictive and statistical analysis for client decision-making. Collaborate with clients to deliver tailored analytics solutions, maintain data integrity, communicate insights through reports and presentations, and support data-driven operational strategies using SAS, Power BI, Tableau, and SQL tools.

Analyze warranty and reliability data to identify trends, risks, and cost drivers; develop dashboards and reports; support root-cause analysis, cost forecasting, and customer negotiations; ensure data integrity and drive continuous improvement across cross-functional teams.

Lead regional economic intelligence and outreach, conduct qualitative and quantitative research, produce sector and district analysis for policy use, prepare publications and presentations, engage senior external stakeholders, and mentor junior economists.

Build and maintain production data pipelines, Airflow DAGs, Snowflake infrastructure, and Data Vault 2.0 models. Ensure data quality, observability, security, governance, reliability, and cost efficiency through automated testing and CI/CD. Lead technical projects end-to-end, collaborate with stakeholders, and support SOX-relevant reporting while developing expertise in commercial insurance data and processes.

Leads healthcare analytics projects using clinical, claims, pharmacy, and eligibility data to evaluate cost, utilization, quality, and program performance. Develops statistical analyses, predictive models, dashboards, and reporting solutions; identifies optimization opportunities; partners with clinical, product, engineering, and business teams; presents recommendations to stakeholders; and mentors junior analysts.

Define and govern enterprise-scale data architecture across batch, streaming, warehouse, lakehouse, transactional, and AI use cases. Establish standards for data quality, lineage, access, cataloging, governance, observability, and SLAs. Architect AI-enabled workflows, resolve complex architecture issues, influence roadmaps, and mentor engineers through hands-on technical leadership. The role requires 15+ years of software, data engineering, or architecture experience and expertise in large-scale data platforms and modeling.

Leads business performance analytics and reporting initiatives, developing Power BI dashboards, KPI frameworks, scorecards, forecasts, and actionable insights. Partners with business leaders to translate needs into reporting solutions, performs root-cause and trend analysis, validates data, establishes governance standards, and mentors analysts. The role combines hands-on reporting development, analytical problem-solving, performance measurement, and cross-functional initiative leadership.

Build and maintain cloud cost monitoring, alerting, and optimization tooling. Develop automation, cost allocation/tagging, data pipelines, dashboards, and integrations with billing APIs. Support FinOps processes, implement cost guardrails, troubleshoot cost systems, participate in on-call rotation, and collaborate with senior engineers and product teams to drive cost-efficient infrastructure and reporting.