Top Data & Analytics Jobs in Detroit, MI

Designs, builds, and optimizes modern Azure and Databricks data platforms for clients. Responsibilities include client discovery, requirements workshops, architecture discussions, batch and streaming ingestion, lakehouse and dimensional modeling, data transformation, governance, monitoring, DevOps, security, and solution reviews. The role also communicates recommendations to technical stakeholders and leadership while delivering scalable analytics and reporting solutions.

The role involves analyzing data in the automotive domain, requiring strong skills in IT security, analysis, organization, and presentation.

The Business Analyst will evaluate business systems, assist with data warehousing, prepare specifications, and optimize processes, requiring extensive experience and creativity.

This role involves analyzing supply chain processes, focusing on purchasing and inventory, and requires report writing and analytical skills.

Develop and maintain Palantir Foundry data pipelines, transformations, analytical workflows, dashboards, and user-facing applications. Analyze and validate data from multiple sources, translate stakeholder requirements into solutions, troubleshoot issues, and support data modeling, testing, documentation, and deployment. Apply Python, SQL, JavaScript or TypeScript, ETL/ELT, cloud, low-code, and UX/UI practices while collaborating with technical teams and government clients.

Designs enterprise data architecture, models, integration patterns, data pipelines, semantic models, governance standards, and access protocols. The role translates business and application needs into scalable data solutions, supports analytics, automation, AI, and application development, and collaborates with data engineers and stakeholders to deliver trusted, reusable datasets.

Architect, build, and evolve AWS-based data platforms and pipelines handling large, complex datasets. Optimize data solutions for scalability, reliability, performance, and cost efficiency. Collaborate with engineering and product teams, make architectural decisions, establish best practices, provide technical mentorship, and support modernization toward intelligent data architectures. The role involves Python, SQL, Databricks, Kubernetes, automation, DevOps, and agentic AI technologies.

Lead client-facing marketing analytics projects using quantitative methods to evaluate offline and digital marketing. Deliver analyses, recommendations, presentations, and advice. Perform Marketing Mix Modeling, Multi-Channel Attribution, Digital Analytics, Pricing/Promotion analysis, demand forecasting, and customer-level analysis. Manage and grow a team. Significant travel required.

Own and operate Priority Waste’s enterprise data platform, building Azure and Microsoft Fabric pipelines, warehouse models, Power BI semantic models and dashboards. Integrate operational, payroll, fleet, telematics, API and file-based data sources. Manage monitoring, alerting, data quality and governance while expanding AI-driven reporting and reconciliation automations. This hands-on, on-site role requires independently scoping, building, deploying and operating production data systems as the company’s primary data engineer.

Supports data pipeline, ETL, integration, validation, reconciliation, monitoring, and troubleshooting activities for insurance claims and enterprise data platforms. Collaborates with engineers, product teams, and business stakeholders to understand requirements, improve data quality, and support scalable cloud-based solutions. Participates in Agile ceremonies and develops technical and insurance-domain expertise through mentoring and project work.