Top Remote Data & Analytics Jobs in Ann Arbor, MI

Design, operate, and scale end-to-end data infrastructure and pipelines. Build reusable data models and a semantic layer, ensure data quality and privacy, implement observability and SLAs, support marketing and growth feeds, partner with cross-functional stakeholders, and enable ML/AI consumption and reverse ETL workflows.

Own and architect the semantic layer and metrics/metadata for the data platform (Databricks/GCP). Build AI-ready models, enforce modeling and documentation standards, implement observability/testing for pipelines, enable self-serve analytics, and collaborate across product, clinical, and business teams to translate questions into reliable data solutions.

The EHSS & Quality Senior Analyst leads data management for EHS, ESG, and Quality goals, ensuring compliance and driving continuous improvement initiatives. Responsibilities include data collection, analysis, and reporting, as well as the development of dashboards and automation processes.

As a Data Analyst Intern, you will assist in data collection, cleaning, analysis, and visualization to support business decisions in a remote setup.

The Senior Data Modeler designs and maintains data models, supports AI-driven practices, and collaborates on data lifecycle processes. Responsibilities include translating business needs into data structures, ensuring data governance, and supporting analytics and AI use cases.

Own and improve the dbt transformation layer, semantic layer, data observability, and pipeline orchestration while migrating the platform to AWS. Ensure data quality and governance to support clinical AI, collaborate with clinical, operations, and finance stakeholders, and audit, document, and fix existing data pipelines.

As a Senior Data Analyst, you will analyze game telemetry data, translate business needs into insights, and guide technical teams. You will also lead exploratory data analysis and maintain data quality practices.

As a Senior Data Engineer, you'll transform raw data into datasets, design production pipelines, integrate customer data, and collaborate with various teams to ensure data quality and reliability.

The Data Ingestion Specialist will manage the ingestion of healthcare data, improve data models, debug issues, and collaborate with team members to maintain pipeline reliability and efficiency.

Owner of data platform modernization: design and migrate legacy systems to Kimball-style dimensional models and star schemas; build reliable production data pipelines; enforce data hygiene and validation; champion dbt best practices; mentor junior engineers; collaborate with analysts and stakeholders to ensure scalable, well-documented data models and platform observability.