Top Analysis Reporting Jobs in Detroit, MI

Owns Voice of Customer measurement, customer research, surveys, segmentation, personas, and family experience metrics. Analyzes qualitative and quantitative feedback, develops actionable insights, supports predictive modeling, and presents recommendations to marketing, operations, and executive stakeholders. The role requires survey design, statistical significance testing, SQL querying, executive communication, and translating customer research into business decisions.

The Senior Data Engineer designs and maintains production data pipelines on GCP using BigQuery, Dataform, Airflow, Dataflow, and Cloud Run. They own data validation, cleansing, troubleshooting, API integrations, and reliable datasets for analytics and AI/ML. The role also involves translating client requirements into data solutions, maintaining dashboards, supporting ad hoc requests, and applying Git, code reviews, and CI/CD practices.

Build and operate governed data pipelines using Microsoft Fabric, Azure, Python, PySpark, Spark, and SQL. Implement Medallion Architecture, ingest data from APIs and enterprise systems, and develop lakehouse and Azure SQL data products supporting analytics and AI. Use Git and CI/CD for deployments, explore AI agentic workloads, and partner with architects and stakeholders to translate requirements into scalable solutions. The role requires local travel, occasional overtime and weekends, and in-person work flexibility.

Designs, develops, and optimizes scalable batch and near-real-time data pipelines and platforms using Snowflake, AWS, Python, DataStage, and Control-M. Builds data models, ensures data quality and governance, tunes performance and costs, supports production operations, and enables analytics and AI/ML use cases. Collaborates with engineering, data science, BI, platform, and business teams in Agile environments.

Leads enterprise data and analytics architecture for a large-scale integration program. Defines target-state platforms, pipelines, integration patterns, data models, governance, security, and reporting layers. Directs vendor teams, approves mappings and semantic models, leads architecture reviews, and validates cutover, performance, scalability, and platform alignment. Requires extensive experience with cloud data platforms, SAP data models, distributed computing, integration methods, governance, security controls, and stakeholder management.

Owns architecture and technical delivery for a healthcare and PBM data platform expansion. Designs Azure Data Factory and Databricks ingestion pipelines for EDI, FHIR, HL7, clinical documents, and pharmacy data. Defines canonical models, metadata-driven frameworks, API patterns, interoperability architecture, trading partner onboarding, and BI data models. Partners with client stakeholders and distributed delivery teams throughout project delivery.

Designs, builds, tests, and supports enterprise data pipelines and Snowflake archival solutions for acquisitions, integrations, reporting, compliance, and analytics. Translates business and technical requirements into mappings, transformations, quality rules, and deployment plans. Collaborates with architecture, security, infrastructure, application, business, and vendor teams. Oversees validation, monitoring, documentation, cutover, go-live readiness, hypercare, and operational handoff while improving reusable, secure, cost-efficient data engineering practices.

Conduct market, competitor, financial, and industry research for the Technology, Media, and Telecommunications practice. Identify prospects, support business development proposals, provide account intelligence, and translate quantitative and qualitative analysis into actionable insights. The role also supports AI-powered research tools and workflows, collaborates with senior leaders, and delivers executive-ready communications in a fast-paced consulting environment.

Develops and maintains Power BI dashboards integrating CMMS and other systems through SQL and APIs. Translates operational and maintenance data into actionable insights for asset reliability, maintenance optimization, compliance, safety, costs, and resource planning. Responsibilities include requirements gathering, application design and integration, testing, training, system enhancements, risk analysis, database management, prototypes, and application lifecycle planning. Requires work across office, plant, and remote sites, including on-call responses and occasional hazardous physical conditions.

Analytics Engineering Intern supporting data modeling, dashboard development, reporting, data quality validation, and business insight generation. The role involves writing SQL, building Looker Studio dashboards, collaborating with stakeholders, presenting findings, and using AI coding assistants responsibly. Candidates must be enrolled in a quantitative undergraduate program and have basic SQL and Git knowledge.