Top Senior Data & Analytics Jobs in Detroit, MI

Design, build, and maintain scalable, secure data architectures, models, and ETL pipelines. Integrate diverse data sources, optimize performance and data quality, implement governance, monitor production SLAs, and collaborate with data scientists, analysts, and product teams. Provide technical leadership, documentation, and training to improve engineering practices across the organization.

The role involves developing insights from data to shape strategies for eyewear and software operations, focusing on customer experience, operational efficiency, and business growth. Collaboration across functions and advanced analytics are key to identify trends and enhance the customer journey.

Build and enhance enterprise analytics and visualization solutions: develop interactive dashboards, data-driven apps, transform and prepare data with Python, implement frontend visualization components with TypeScript, integrate with Microsoft and Google enterprise ecosystems, and use AI tools to accelerate development while collaborating with stakeholders and owning deliverables end-to-end.

Architect and implement scalable Azure Lakehouse solutions (Databricks, Microsoft Fabric). Lead cloud data migrations, build ETL/ELT and streaming pipelines, enforce data governance and security, advise clients, run workshops, and mentor teams while managing multiple engagements.

Responsible for compiling, cleaning, enriching, analyzing, and visualizing sales and pipeline data across systems. Build forecasting models, dashboards, and reports; present insights to stakeholders and collaborate cross-functionally to improve processes and reporting.

Architect and deploy scalable Inventa data-management solutions, lead complex enterprise integrations (APIs, on-prem, cloud, SaaS, data lakes), resolve architectural performance and access issues, create global architecture guides and documentation, and feed product improvements through field insights. Customer-facing, cross-functional collaboration with Sales, Customer Success, and Product.

Lead development of cloud data platforms and end-to-end data pipelines using AWS/Snowflake and big-data technologies (Spark, Hive, Iceberg). Automate builds and deployments with Bash/Python shell scripting, apply CI/CD and Medallion Architecture, perform data modeling and warehousing, and collaborate across teams. Pharma/AbbVie experience preferred.

Lead building a data- and AI-enabled growth engine to improve pipeline quality and visibility. Define data governance, segmentation, scoring, and KPIs; operationalize demand-generation campaigns and tooling; prototype AI-driven automation and reporting; partner with vendors and sales/marketing to measure and improve pipeline conversion and ROI.

Provide hands-on support for procurement and finance systems: implement and optimize ERP/source-to-pay platforms, maintain master data, validate reporting, troubleshoot issues, support system upgrades, automation, BI/dashboard development, and change management to ensure data integrity and operational efficiency across finance and procurement.

Build and maintain GCP-based data pipelines and foundational tables (BigQuery, Dataform, Dataplex). Merge financial and ERP datasets, define metrics, deliver reports and analyses, and collaborate cross-functionally to support decision-making and business measurement.