Senior Data Engineer: Azure Lakehouse & AI Pipelines (Remote)

Detroit Startup Council; Dearborn (MI); Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

401(k) with employer matching

Paid time off and holidays

Job summary

Carhartt in Dearborn, MI is seeking a Sr. Data Engineer to design, build, and optimize data solutions using Azure Databricks and Lakehouse architecture.

You will mentor engineers and collaborate with analytics, security, and product teams to deliver trusted data for reporting, analytics, ML, and operational use. The role emphasizes scalable pipelines, governance, and quality, with production-grade tooling, CI/CD, and cloud-native services.

Qualifications

• Bachelor’s degree in a technical field or equivalent experience.
• 8+ years of professional data engineering experience.
• Experience designing and implementing enterprise data solutions on Azure Databricks and Lakehouse.

Responsibilities

• Design, build, test, deploy, and support scalable data pipelines on Azure Databricks.
• Develop Lakehouse architecture using Delta Lake and ADLS with reusable data products.
• Create and optimize data models from conceptual to physical for analytics.
• Implement orchestration, monitoring, logging, and data lineage for production workloads.
• Apply data governance, security, privacy, retention, and access controls.
• Mentor engineers, lead design reviews, and collaborate across teams.

Skills

Azure Databricks

PySpark

Python

SQL

Delta Lake

Azure Data Factory

Data modeling

Data governance

CI/CD

Git

Azure Data Lake Storage

Unity Catalog

Education

Bachelor’s Degree in Computer Science, Information Systems, Engineering, Data Science, or related field

Graduate degree preferred

Tools

Azure DevOps

SAP integration

Job description

Carhartt in Dearborn, MI is seeking a Sr. Data Engineer to design, build, and optimize data solutions using Azure Databricks and Lakehouse architecture.

You will mentor engineers and collaborate with analytics, security, and product teams to deliver trusted data for reporting, analytics, ML, and operational use. The role emphasizes scalable pipelines, governance, and quality, with production-grade tooling, CI/CD, and cloud-native services.