Top Remote Data & Analytics Jobs in Detroit, MI

Own and evolve the analytics platform, including data models, pipelines, metric definitions, semantic layers, dashboards, and self-service data products. Partner with cross-functional stakeholders to translate business needs into reliable technical solutions. Lead data initiatives, improve ELT reliability and governance, resolve quality issues, mentor teammates, and shape the Analytics team’s technical roadmap. The role requires strong SQL, dbt, modern data-stack experience, business communication, and independent execution in an ambiguous environment.

Analyze web, journey, survey, and marketing data to uncover actionable insights for enterprise clients. Translate technical findings into business recommendations, test-and-learn plans, dashboards, reports, and presentations. Collaborate with account teams, ensure data quality and statistical rigor, investigate anomalies, and support client questions. The role requires expertise in analytics platforms, data visualization, spreadsheets, SEO, and client-facing data storytelling in a fast-paced SaaS environment.

Own analytics, modeling, reporting, and recommendations for portfolio management. Design underwriting and pricing for multicard and line-extension strategies, test rewards upgrades and purchase incentives to boost engagement, and partner with risk, data science, and engineering to operationalize strategies and defend recommendations to stakeholders.

Leads enterprise analytical modeling and semantic architecture, establishes standards for testing, documentation, governance, lineage, observability, and access, and develops reusable governed data products. Partners across Product, Engineering, Finance, Clinical, Research, Marketing, and AI teams; guides architecture reviews, data quality ownership, semantic layer design, and governance adoption. Mentors engineers and drives modernization of analytical environments.

Provides strategic and technical leadership for integrated data architecture, performance dashboards, data governance, analytics, verification tools, and data quality processes in Uganda. Translates program requirements into system and analytical specifications, integrates government data sources, identifies risks through data triangulation, and supervises information systems, monitoring and evaluation, and analytics managers. The role also supports government engagement, institutional ownership, proposal development, stakeholder relations, and team growth.

Leads Versapay’s enterprise data strategy, architecture, governance, quality, accessibility, and commercialization. The role unifies transactional and analytical data, establishes semantic models and data catalogs, enables secure AI and agentic capabilities, develops external data products, manages data platform costs, and leads teams across data engineering, analytics, BI, and platform operations. The Senior Director partners with executive, product, engineering, commercial, finance, legal, and compliance stakeholders.

Supports Indonesian and broader Asian survey operations by monitoring data quality, managing quality-control staff, correcting survey issues, analyzing collection progress, and developing data-quality tools. Coordinates field operations, training, stakeholder engagement, translations, and backcheck processes. Provides insights on coffee and cacao sustainability data to country teams and supply-chain stakeholders. The role is fully remote from Indonesia with travel to regional agricultural areas.

Supports the design and development of scalable end-to-end data pipelines and cloud data platforms. Responsibilities include improving data reliability and quality, implementing data management practices, supporting automation and process improvements, ensuring secure and cost-effective solutions, and recommending system enhancements. The intern collaborates with global teams and gains hands-on experience in data engineering, project coordination, and innovation management.

Build and maintain a global knowledge base of electronic-resource metadata. Responsibilities include analyzing publisher data, creating and maintaining collections, establishing data feeds, researching missing metadata, documenting transformation processes, resolving data issues through root-cause analysis, coordinating with vendors, and managing workload priorities. The role requires advanced Excel skills, attention to data quality, strong communication, and familiarity with metadata standards.

The Principal Data Engineer designs and builds scalable cloud-native data platforms, pipelines, frameworks, and governed data products supporting analytics, reporting, AI, and operational workloads. Responsibilities include Databricks, Spark, Delta Lake, Azure, SQL Server, batch and streaming processing, data integration, performance optimization, governance, modernization, troubleshooting, architecture reviews, and mentorship. The role provides senior technical leadership without direct people management and supports insurance-domain data across policy, claims, billing, finance, and regulatory functions.