Top Remote Analysis Reporting Jobs in Detroit, MI

The Data Engineer will build and maintain data pipelines, optimize workflows, manage infrastructure, and enhance pipeline observability while collaborating with teams for effective data delivery.

Lead the evolution of data platform by designing scalable pipelines, improving data processes, mentoring teams, and modernizing data architecture.

Lead the enterprise data platform strategy and architecture, driving Snowflake/dbt-based platform evolution, self-service Data Mesh and medallion models. Build AI-ready pipelines, RAG systems, and observability/cost frameworks while managing a central data team, supporting federated BI, and executing hands-on technical work.

This role drives data-driven decision-making in product analytics, collaborating with cross-functional teams to generate actionable insights and evaluate new launches to enhance platform growth.

Own BI analytics using a modern data stack to generate insights, build dashboards and self-serve tools, partner with stakeholders, and deploy AI-driven reporting and natural-language query solutions.

Build and maintain scalable, governed data pipelines from ingestion through transformation and integration. Implement schema validation, data quality checks, job monitoring, and production-grade APIs. Work with Python, SQL, Airflow, dbt, AWS (EMR, Athena, S3), Iceberg/Parquet, and contribute to CI/CD, observability, and on-call support while collaborating with analytics and product teams.

The Senior Staff Data Engineer will design scalable data systems, lead technical direction, optimize data platforms, and ensure data quality and performance for Observability & Insights.

Design, build, and maintain end-to-end data models and pipelines to support CX operations, compliance reporting, and customer insights. Create dashboards and metrics, enforce data quality and governance, automate recurring workflows, and partner with stakeholders and broader data teams to deliver self-serve analytics solutions.

Design and manage assessment blueprints and items end-to-end, apply psychometric rigor (equating, calibration, reliability/validity), run item/test analyses, lead vendor/SME collaboration, maintain standards and QA, and own documentation and continuous improvement of the assessment portfolio.

The Data Engineer will help build modern data infrastructure, designing ETL pipelines, modeling datasets, and collaborating with teams for improved data quality and accessibility.