Top Senior Data & Analytics Jobs in Detroit, MI

Design, architect, and implement end-to-end data ingestion, storage, modeling, and provisioning solutions on the GE Predix platform. Lead cross-functional teams, set data architecture standards, develop OLTP/OLAP models, perform POCs, and enable analytics at scale while enforcing data management policies.

Design, build, and maintain enterprise analytics solutions and semantic data models using Microsoft Fabric, Databricks, SQL, Python, and Power BI. Develop reporting datasets, dashboards, and self-service analytics; ensure data quality, performance, CI/CD, and governance; translate business requirements into scalable solutions; provide technical leadership, mentor engineers, and collaborate with architects and stakeholders to align analytics with business objectives.

Perform technical business analysis supporting ETL and data operations. Write complex SQL queries, manage and analyze data, gather technical business requirements, and facilitate stakeholder meetings. Work independently in a customer/technical support environment using Excel and Agile/Waterfall methodologies, applying strong problem-solving and attention to detail.

Manages client, compliance, and performance reporting across healthcare programs using eligibility and claims data. Leads reporting analysts while remaining hands-on with advanced SQL, dashboards, data crosswalks, validation, reconciliation, root-cause analysis, and data-quality monitoring. Partners with data engineering and clients to resolve upstream issues, establish reporting standards, and guide the analytics roadmap.

Architect and maintain NetBrain’s first cloud data warehouse, ELT pipelines, transformation layer, semantic models, and BI foundation. Own data quality, governance, lineage, access controls, and curated models supporting product usage, customer adoption, account health, and go-to-market reporting. Partner with stakeholders to establish reliable metrics and a standardized source of truth, while supporting AI-assisted analytics and natural-language reporting use cases.

Leads advanced analytics for Airbnb’s Community Blueprint Quality team. Responsibilities include diagnosing customer experience issues, designing experiments, applying causal inference, developing metrics, using LLMs to analyze unstructured data, building dashboards and analytical artifacts, and translating complex findings into recommendations for senior leadership. The role partners cross-functionally with Product, Engineering, Data Science, Data Engineering, Operations, and Finance.

Lead marketing analytics for Airbnb’s loyalty and community pilot, designing experiments, measuring incremental impact, analyzing customer and campaign performance, and delivering recommendations to senior leadership. Partner with Marketing, Finance, Data Science, Product, and Operations to optimize investment across growth initiatives and expand experimentation across business lines.

Leads enterprise data strategy, platform architecture, Master Data Management, federated governance, data quality, compliance, and real-time analytics. Builds scalable data infrastructure, modernizes legacy pipelines, establishes operational data hubs, and enables secure data products across the enterprise. Oversees data engineering, architecture, MDM, governance, and embedded analytics teams while partnering with executives and business units to drive transformation, operational efficiency, AI readiness, and acquisition integration.

Build and maintain data models, pipelines, metrics, dashboards, and analytics supporting identity graph construction, entity matching, and identity resolution. Partner with engineering and data science teams to productionize matching logic, evaluate match quality, monitor data quality and drift, and manage identity-provider relationships. Translate complex identity concepts into actionable insights for technical and non-technical stakeholders while helping define privacy-conscious product and data priorities.

Design and lead scalable, secure, highly available database infrastructure for multi-terabyte SQL Server environments. Set technical direction for data architecture, performance, real-time pipelines, security, and growth. Troubleshoot complex production issues, optimize queries and indexes, guide cross-functional projects, mentor engineers, review changes, reduce technical debt, and evaluate emerging technologies. Monitor database health using Splunk, Datadog, and Grafana while influencing engineering and Site Reliability strategy.

Develops and maintains data pipelines, datasets, schemas, models, databases, and data flows. Analyzes raw and structured data, improves data quality, builds reporting and data dictionaries, and collaborates with analysts, scientists, and stakeholders. The role supports data security, compliance, visualization, and reporting while modernizing legacy technologies. Requires a flexible schedule supporting 24/7/365 operations and the ability to obtain and maintain a security clearance.