Top Remote Data & Analytics Jobs in Detroit, MI

Design, build, and maintain scalable Databricks-based data pipelines and ELT workflows; develop and document dbt models; define data modeling methodology; ensure data quality, reliability, and scalability; collaborate with clients and cross-functional teams; provide technical guidance and deliver improvements to clients' data infrastructure and analytics capabilities.

As a Data Engineer, you will build and optimize data pipelines, ensuring accurate data delivery that informs pricing and market analytics at Alt.

The Strategy Analyst provides analysis and strategic recommendations to enhance sales, underwriting, marketing, and operations, leveraging data to drive business growth and improve operational efficiency.

General application to Cardamom's talent pipeline for roles across Epic analytics, data & analytics, project/product management, and internal functions. Candidates can submit for Epic analyst, data engineering, data science, interoperability, BI, software development, and entry-level roles (Madison local). Talent team reviews submissions and contacts matches for current or upcoming openings.

The Solutions Architect will lead the creation of AI-driven tools and data models, partnering with teams to transform complex datasets into actionable insights and developing robust dashboards and frameworks to empower business solutions.

Manage the end-to-end data issue lifecycle for North America: intake, triage, root cause analysis, remediation planning and execution oversight. Produce IMR reporting and dashboards, maintain audit-ready records, engage stakeholders, and improve IMR processes and tooling to strengthen data quality and controls.

The Solutions Consultant will conduct product demos, assist in sales cycles, and provide evidence of product value while maintaining product knowledge and client relations.

The Business Analyst will gather requirements from clients, support project lifecycles, conduct demos, and manage change, while utilizing ServiceNow. Responsibilities include documentation and relationship building.

Own support analytics for User Operations: build dashboards and recurring reports, track north-star metrics (cSAT, TTR, QA, escalations), instrument Zendesk, connect support to product/customer data, quantify operational costs of bugs, and measure AI-driven support performance.

Own and maintain data products end-to-end for sector teams, analyze large datasets, refine methodologies, automate workflows using AI and tooling, collaborate with Research, Engineering, and Product, and deliver accurate, client-facing insights and improvements.