Top Remote Data & Analytics Jobs in Detroit, MI

The Data Engineer Consultant will design and implement scalable data solutions, advise clients on optimizing data environments, and develop ETL pipelines and data models to support business objectives.

Lead and expand the company's BI and analytics capabilities: set data strategy with senior leadership, manage analytics pipeline and BI stack, implement data governance, mentor and grow BI and data engineering teams, partner cross-functionally to drive data-informed decisions, and manage vendors and processes for scalability.

Partner with hospitality leadership across 40+ amphitheaters to deliver BI and analytics: build dashboards, inform pricing and concessions strategy, analyze labor and cost, support data integrity, run experiments, and act as a live-music subject matter expert to drive operational improvements and client relationships.

Early member of the Data & Analytics team responsible for end-to-end analyses and data products. Build and maintain dbt models, semantic layers, and dashboards (Power BI). Partner with Finance, Merchandising, Marketing, Operations and others; own metric definitions, validate AI-generated SQL/dbt/Python, investigate data discrepancies, and help evolve Snowflake-based data infrastructure and governance.

The Senior Data Engineer will develop data engineering solutions, manage ETL workflows, and establish a new data practice while collaborating with stakeholders.

The Data Architect will design scalable data models, transform raw data into actionable insights, and deploy analytics solutions for healthcare providers, with a strong emphasis on SQL proficiency and cloud technologies.

As a Senior GTM Data Scientist, you will develop predictive models, analyze experiments, and provide actionable insights to GTM teams.

The Staff Data Engineer will lead financial data operations, ensuring accuracy and reliability of data pipelines, while collaborating with Finance, Product, and Engineering teams to enhance systems and decision-making processes.

The Lead Risk Analytics Data Scientist will develop risk pricing, design data models, automate workflows, and communicate insights to leadership. Responsibilities include owning the risk narrative, building analytics foundations, and utilizing AI to enhance efficiency.

Perform data extraction from SQL/NoSQL systems, validate and transform data, and run statistical and psychometric analyses (IRT, reliability, norming). Validate assessment logic, define quality metrics, design research and simulation studies, and present findings via reports and dashboards. Collaborate cross-functionally and maintain current psychometric and data engineering practices.