Data Engineering Lead: Modernize Pipelines & Drive CI/CD

Safelite; North Carolina; On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Competitive weekly pay

Benefits valued over $10k (401(k),+)

Tuition reimbursement

Job summary

Safelite is seeking a Manager of Data Engineering to modernize legacy data pipelines, oversee data ingestion and CI/CD, and act as a player-coach for a team of data engineers. You will drive scalable ETL, a centralized data lake, and proactive governance to ensure data availability for analytics and embedded users.

The role requires 4–6 years in data engineering with 1–3 years in leadership, strong SQL and Python, and hands-on experience with AWS Glue, Informatica, Snowflake, and Airflow.

Qualifications

• Bachelor's degree in CS, engineering, analytics, or related field.
• 4–6 years hands-on data engineering/analytics experience.
• 1–3 years managing a technical team.
• Experience with ETL/ELT, data pipelines, and modern tooling.
• Strong SQL, Python, and data governance knowledge.

Responsibilities

• Modernize legacy ingestion processes with scalable ETL.
• Design pipelines to central data lake.
• Develop CI/CD for data workflows; monitor and alerting.
• Rebuild legacy reporting workflows with modern cloud tools.
• Mentor data engineers and lead training.
• Collaborate across orgs to align data initiatives.
• Manage data infrastructure costs.
• Perform other duties as assigned.
• Complies with policies.

Skills

Leadership

Data architecture

SQL proficiency

Python

Cross-functional collaboration

Project management

Education

Bachelor's degree in CS/Engineering/Analytics

Tools

Buildkite

Snowflake

BigQuery

Airflow

Dagster

GitHub

Job description

Safelite is seeking a Manager of Data Engineering to modernize legacy data pipelines, oversee data ingestion and CI/CD, and act as a player-coach for a team of data engineers. You will drive scalable ETL, a centralized data lake, and proactive governance to ensure data availability for analytics and embedded users.

The role requires 4–6 years in data engineering with 1–3 years in leadership, strong SQL and Python, and hands-on experience with AWS Glue, Informatica, Snowflake, and Airflow.