Top Senior Data & Analytics Jobs in Detroit, MI

Build and own the data platform backbone: design ingestion patterns, Snowflake warehouses, governance, and freshness strategy. Implement reliable batch and streaming pipelines, data quality, observability, and onboarding processes. Lead legacy migrations, create data contracts and SLAs, and apply AI-native tooling to automate debugging, documentation, and operational workflows while partnering with Analytics, Engineering, and vendors.

Design and build Snowflake transformation layer and migrate legacy SQL to versioned dbt models. Define conformed dimensions/facts using Kimball principles, set modeling and CI/CD standards, implement data quality/lineage, support BI migration and AI/ML readiness, and mentor future hires. Hands-on work in dbt, SQL, and Python with stakeholder collaboration and governance for financial and operational data.

The role involves acting as a subject matter expert in Data and AI, providing technical expertise during sales processes for Azure-based solutions, and mentoring team members to enhance client experiences.

Lead design and implementation of the commercial data and systems foundation for launch and growth. Own Salesforce-led commercial systems, integrations, data warehouse, MDM, analytics enablement, governance, and scalable delivery to support commercial operations, reporting, and compliance.

Lead market and client-level fundraising data analysis and publish original research and benchmarks. Partner with Sales, Customer Success, and Marketing to produce ROI cases, client insights, and thought leadership. Present findings publicly at conferences, build repeatable insight frameworks and tools, and translate data into persuasive narratives for advancement leaders.

Lead a team delivering actuarial statistical reporting, regulatory submissions, and analytics. Ensure compliance with bureau requirements, drive automated reporting and UAT for policy/claims systems (Guidewire, Solartis), partner with actuarial, technology, and vendors, and manage stakeholder/regulator interactions while mentoring staff and improving data governance and reporting processes.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

Lead design and implementation of Jane's customer data infrastructure: own event collection, pipelines, CDP tooling, schema governance, identity resolution, and attribution. Work cross-functionally with marketing, BI, product, and engineering to set standards, evaluate tooling (e.g., RudderStack), ensure privacy-compliant instrumentation, and build reliable, consistent data delivery to the warehouse.

Build and maintain P&C actuarial pricing models and indication reports; refine pricing methodologies; analyze large datasets; automate workflows with Python, SQL, and Excel; create dashboards and presentations; collaborate with underwriters, claims, program teams, and reinsurers; and drive process and methodology improvements.

The Senior Analytics Engineering Manager will oversee analytics engineering vision, manage a team, ensure data quality, and drive data-driven decisions across departments.