Lead Data Engineer: Cloud Data Platforms & AI

Brooksource; Detroit (MI); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

401(k) Matching Plan

Paid Holidays

Health, Dental, Vision Insurance

Job summary

You will design and implement ingestion, transformation, and quality processes for structured and unstructured data, guiding teams across data architecture, APIs, and large-scale integration. The role emphasizes leadership, robust engineering standards, and a focus on Insurance data capabilities.

Qualifications

• 8+ years of data engineering experience, including analytics-focused data warehouse environments such as Snowflake.
• Experience delivering cloud-based data platforms and scalable data pipelines in enterprise settings.
• Strong data modeling skills, including Data Vault, and data governance practices.

Responsibilities

• Lead and manage the Data Engineering squad, setting scalable platform standards.
• Design, build, and optimize modern data pipelines and enterprise data solutions.
• Develop cloud-based data engineering solutions (data lakes, data warehouses, data platforms).
• Design scalable data structures and Data Vault modeling for auditable data assets.
• Build data ingestion, transformation, preparation, and quality processes across data sources.
• Develop large-scale data integration, API-based services, and NoSQL/SQL processing.
• Enable trusted data for analytics, ML, and AI use cases across Insurance data domains.
• Partner with business and IT to align data requirements with enterprise priorities.
• Advance Insurance Data and Analytics platform capabilities through governance-aligned engineering.

Skills

Cloud data platforms

Data engineering leadership

Snowflake

AWS S3

dbt

Data Vault

APIs

Python

DevOps

Git

Education

Bachelor’s degree in CS/IS

Advanced degree preferred

Tools

InfoSphere DataStage

Qlik Replicate

CP4D

AWS CLI

Lambda

DynamoDB

Job description

You will design and implement ingestion, transformation, and quality processes for structured and unstructured data, guiding teams across data architecture, APIs, and large-scale integration. The role emphasizes leadership, robust engineering standards, and a focus on Insurance data capabilities.