Lead Data Engineer: Data Products & Lakehouse

Protective Life; United States; On-site; USD 110,000 - 168,000; Full time

Benefits offered by this job

Health, dental, vision insurance

401(k) with company match

Paid time away (vacation, parental)

Job summary

Protective is seeking a Lead Data Engineer to set the technical direction for a delivery pod building data products on Voyager, our Databricks lakehouse on Azure. You will lead the design of data products through Bronze, Silver, and Gold layers and own how the pod's data products are modeled, contracted, and tested.

This is a hands-on leadership role where you still write and review production code daily. You will mentor engineers, partner with ML teams, and drive quality, observability, and

Qualifications

• Bachelor’s degree or equivalent practical experience in a related field.
• 6+ years building and operating production data pipelines and data models.
• Strong Python and SQL with ability to write/review production code.
• Hands-on experience with Databricks and lakehouse architectures.

Responsibilities

• Lead the design of data products end to end across Bronze/Silver/Gold layers.
• Own data contracts, consumer compatibility, and breaking-change policies.
• Set engineering standards for Python/SQL/dbt and CI/CD gates.
• Lead design reviews, ensure quality tests, and observable pipelines.
• Collaborate with ML teams and platform to improve data product delivery.

Skills

Python

SQL

Databricks

Delta Lake

Dimensional modeling

Data contracts

Code reviews

SLA/SLO guidance

Technical leadership

Education

Bachelor's degree in CS/IS/Engineering

Tools

Dagster

Airflow

Azure DevOps

Unity Catalog

dbt

Delta Lake

Job description

Protective is seeking a Lead Data Engineer to set the technical direction for a delivery pod building data products on Voyager, our Databricks lakehouse on Azure. You will lead the design of data products through Bronze, Silver, and Gold layers and own how the pod's data products are modeled, contracted, and tested.

This is a hands-on leadership role where you still write and review production code daily. You will mentor engineers, partner with ML teams, and drive quality, observability, and