Top Data & Analytics Jobs in Detroit, MI

Supports actuarial financial data systems and marts through data-set development, SQL testing, monthly refreshes, validation, quality assurance, reporting, and claims data analysis. The role gathers requirements, resolves system issues, documents technical specifications, develops decision-support solutions, and assists senior team members with business projects. Healthcare claims, Snowflake, and AWS experience are beneficial.

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.

Architects, develops, deploys, and optimizes enterprise-scale data platforms, schemas, pipelines, data models, and integrations. Leads SQL engineering, ETL/ELT frameworks, API ingestion, cloud-native solutions, database performance tuning, analytics, business intelligence, and data governance. Supports Power BI and other BI tools while providing technical leadership across data engineering initiatives. Knowledge of disputes, chargebacks, fraud operations, and case-management systems is preferred.

Design and scale batch and streaming data pipelines, ETL/ELT workflows, data models, warehouses, quality frameworks, dashboards, and AI/ML feature pipelines. Automate reporting and analytics while collaborating with product, engineering, and operations teams. The role also includes internal consulting practice participation, thought leadership, client case studies, and contribution to digital transformation initiatives.

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.

Administers Informix, MySQL, and other databases across cloud and hybrid environments. Responsibilities include configuration, maintenance, performance tuning, security remediation, replication, monitoring, Tier 3 support, schema changes, migrations, SQL data extraction, backup recovery testing, automation, compliance, and collaboration with engineering, architecture, security, and application teams.

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.

Analyze raw usage, identity, license, and cost data from cloud, SaaS, and observability sources. Profile and map data to canonical schemas, design transformation and cost-allocation logic, assess application attribution, derive business taxonomies, and reconcile observed usage with vendor invoices. Contribute to FOCUS alignment, attribution precedence, shared-endpoint allocation, coverage reporting, and data quality specifications for engineering implementation.

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 advanced advertising measurement programs, including incrementality, conversion lift, multi-touch attribution, and optimization analysis. Translates complex datasets into media recommendations, executive presentations, case studies, and go-to-market narratives. Partners with sales, product, data science, and GTM teams to expand measurement adoption, manages external research vendors, and develops AI-enabled reporting and sales-enablement workflows.