Top Data & Analytics Jobs in Detroit, MI

Clean and reconcile employee master data and historical leave records from multiple sources. Define standardized HR data structures, establish validation and access controls, and automate leave request, approval, and balance tracking workflows using Google Workspace or a suitable alternative. Document maintenance processes and support potential expansion across international branches. The contractor will independently manage the fixed-scope project, propose an RFQ, and provide timeline, hours, costs, assumptions, and deliverables.

Leads enterprise Snowflake architecture, administration, governance, security, performance, and cost optimization across AWS and Azure. Manages Snowflake administrators and data engineers, serves as Product Owner, and leads delivery for federal and public-sector clients. Responsibilities include stakeholder management, technical escalations, data integration, agile backlog prioritization, risk and SOW management, and executive engagement.

Maintains and optimizes actuarial data marts, performs financial data refreshes and quality checks, develops SQL-based claims data solutions, and supports reporting, audits, business requirements, application configuration, and project teams. Serves as a technical lead and liaison among actuarial, business, and vendor stakeholders while ensuring data accuracy, completeness, and auditability.

Leads enterprise data engineering and platform execution, including modernization roadmaps, cloud transformation, governance, reliability, operational excellence, budgets, vendors, and investment prioritization. Directs multiple engineering managers and teams across platform engineering, data engineering, integration, and operations. Partners with architecture, security, compliance, analytics, clinical, product, finance, and business leaders to deliver secure, scalable, resilient data capabilities supporting AI, interoperability, reporting, and digital transformation.

Build and operate scalable cloud data pipelines, warehouses, transformation layers, and ML production systems. Lead data infrastructure architecture, warehouse performance optimization, DataOps monitoring, CI/CD improvements, data quality testing, and large-scale data product delivery. Collaborate across teams, promote data stewardship, and support batch and streaming pipelines while deploying, serving, and monitoring machine learning models.

Build and maintain Databricks data pipelines across bronze, silver, and gold layers. Ingest APIs, logs, billing exports, and reference data; implement attribution logic, governance, data quality monitoring, and cost optimization. Manage Unity Catalog permissions, lineage, refresh schedules, incremental processing, and CI/CD workflows while supporting multi-cloud storage and high-volume caller-identity data.

Own the architecture and technical direction of Northbeam’s data ingestion and integration platform. Design scalable API-based ETL, event-driven and batch processing systems; establish standards for observability, freshness, and failure handling; and guide build-versus-buy decisions. Collaborate across engineering, infrastructure, product, and business teams while mentoring engineers, leading design reviews, and driving complex platform initiatives to completion.

Analyze performance marketing and subscription-funnel data, including acquisition efficiency, conversion, retention, churn, and customer lifetime value. Build automated Domo dashboards and governed reporting pipelines from multiple data sources. Investigate data anomalies, analyze A/B tests, define KPIs, and communicate insights to executives. Partner with marketing, product, engineering, finance, agencies, and BI contractors while independently executing analytics projects and improving reporting workflows.

Leads consumer and market insights for Yahoo Ads, partnering with sales and go-to-market teams to develop data-driven narratives, audience profiles, vertical trends, case studies, and client materials. Uses Yahoo first-party data, syndicated research, quantitative and qualitative methods, and generative AI tools to accelerate research. Builds validated analytical templates and self-service resources, collaborates on reporting pipelines and dashboards, and translates complex findings into executive-ready presentations.

Leads and builds Instructure’s decision science function, including hiring, team development, roadmap ownership, experimentation, causal and predictive modeling, executive insights, and data literacy. Partners with product, engineering, marketing, finance, and executives to guide product, pricing, retention, go-to-market, and operational decisions. Establishes analytical standards, supports data infrastructure, and ensures ethical, privacy-conscious use of student data.