Data Engineering Manager: Cloud Platforms & AI Leadership

IPolarity LLC; Detroit (MI); Hybrid; USD 150,000 - 190,000; Full time

Job summary

IPolarity LLC in Detroit, MI is seeking a Manager Data Engineer to lead the Data Engineering squad, build scalable pipelines, and deliver cloud-based data solutions. This is a potential contract-to-hire role, with a hybrid schedule (3 days per week in the office) and an emphasis on governance, Data Vault modeling, and enterprise analytics.

The ideal candidate has 8+ years in data engineering, deep Snowflake experience, and strong leadership.

Qualifications

• 8+ years of progressive experience in data engineering, including analytics-focused data warehouse environments like Snowflake.
• Experience delivering cloud-based data platforms on AWS (S3, Lambda, DynamoDB).
• Strong data modeling skills with Data Vault and enterprise data architectures.
• Proven leadership in building scalable data pipelines and API-based data services.
• Experience with data ingestion, transformation, quality, and governance.

Responsibilities

• Lead and manage the Data Engineering squad, focusing on scalable platforms and engineer growth.
• Design, build, and optimize modern data pipelines and enterprise data solutions that support analytics and AI use cases.
• Develop cloud-based data architectures, data lakes, and cloud data warehouses.
• Implement Data Vault modeling to enable auditable, resilient data solutions.
• Build and maintain data ingestion, transformation, quality, and governance processes.

Skills

Data leadership

Cloud data platforms

Data engineering

Python

Git

DevOps

Data Vault

Education

Bachelor's degree in Computer Science / Information Systems

Tools

Snowflake

AWS

S3

Lambda

DynamoDB

dbt

Qlik Replicate

InfoSphere DataStage

CP4D

Git

Job description

IPolarity LLC in Detroit, MI is seeking a Manager Data Engineer to lead the Data Engineering squad, build scalable pipelines, and deliver cloud-based data solutions. This is a potential contract-to-hire role, with a hybrid schedule (3 days per week in the office) and an emphasis on governance, Data Vault modeling, and enterprise analytics.

The ideal candidate has 8+ years in data engineering, deep Snowflake experience, and strong leadership.