Senior Data Engineering Lead - Big Data & GCP

American Family Insurance Agency Staff; Englewood (CO); On-site; USD 131,000 - 220,000; Full time

Job summary

American Family Insurance seeks a data engineering leader to architect and drive scalable data pipelines within our big data platform in Englewood, CO. You will lead an engineering team, ensure data quality and security, and collaborate with application architecture and development teams.

The role emphasizes hands-on Python ETL work, GCP, Spark/Hadoop, SQL/NoSQL, and open‑source ML tooling, with opportunities to advance data modeling and operational excellence.

Qualifications

• Hands-on experience building data pipelines and platforms.
• Experience with data governance, security and privacy practices.
• Strong SQL/NoSQL knowledge across multiple data stores.

Responsibilities

• Leads an engineering team to meet project deadlines and priorities.
• Supervises data engineering team members and activities.
• Ensures data quality, security, privacy, and integrity across the data lifecycle.
• Documents critical workflows and operational support aspects of team responsibilities.
• Develops deep understanding of data sources, granularity, availability, and limitations.
• Provides proactive technical oversight and advice to architecture and development teams to enable scale and reuse.
• Creates maintainable, scalable code to load and manipulate data in the data warehouse.
• Facilitates communication with project teams and stakeholders.

Skills

GCP

Python

SQL/NoSQL

ETL pipelines

Spark/Hadoop

Machine learning tools

Data modeling

CI/CD

Web services

Infra as code

Tools

Docker

CloudFormation

Terraform

Git

Jenkins

Job description

American Family Insurance seeks a data engineering leader to architect and drive scalable data pipelines within our big data platform in Englewood, CO. You will lead an engineering team, ensure data quality and security, and collaborate with application architecture and development teams.

The role emphasizes hands-on Python ETL work, GCP, Spark/Hadoop, SQL/NoSQL, and open‑source ML tooling, with opportunities to advance data modeling and operational excellence.