Top Senior Analysis Reporting Jobs in Detroit, MI

Leads analysis of Ford and Lincoln customer cohorts across the app ownership journey, identifying engagement, conversion, retention, and value trends. Defines KPI frameworks, develops executive dashboards and scorecards, forecasts performance, and identifies early risks and opportunities. Partners with strategy, product, marketing, finance, analytics, and data engineering teams to translate customer behavior into actionable business recommendations and improve decision-making.

Leads Ascent’s data practice, including DBAs, analysts, and engineers; owns the data roadmap, warehouse, Snowflake modeling, integrations, governance, reporting modernization, data quality, backup, retention, budget, and delivery standards. Partners with software teams, resolves complex data issues, supports customer-facing reporting, coaches staff, manages offshore teams, and introduces AI tools into development and delivery.

Design, build, and optimize enterprise Power BI reports, dashboards, semantic models, and DAX measures. Manage Power BI Service workspaces, security, deployment pipelines, refreshes, and gateways. Integrate data from ERP, manufacturing, supply chain, finance, warehouses, and lakes while improving performance through model optimization, aggregations, and incremental refresh. Partner with stakeholders and data engineers to establish governance, translate requirements, and enable adoption through documentation and training.

Hands-on senior data engineer to build and scale GCP-based data pipelines, BigQuery analytical models, Terraform-managed infrastructure, and BI/reporting surfaces. Must handle healthcare claims/PHI securely, implement observability and compliance controls, and collaborate cross-functionally to deliver reliable data products and support future AI/ML initiatives.

Build and scale data pipelines supporting Vehicle Configuration Optimization. Ingest and transform Snowflake data into Databricks using Bronze, Silver, and Gold medallion layers. Develop Python and SQL ETL/ELT workflows, monitor pipeline health, optimize performance, and implement data quality and governance controls. Partner with data scientists, analysts, and stakeholders to produce curated datasets for analytics, simulation, and machine learning.

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.

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.