Lead Data Engineer: Build Data Products on Databricks

Protective; Nebraska; Hybrid; USD 110,000 - 168,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Mental health benefits

Paid time off

Parental leave

Short-term disability

401(k) matching

ProHealth Rewards

Job summary

Protective is seeking a Lead Data Engineer to define technical direction for a data product pod on Voyager, our Databricks lakehouse on Azure. You will own end-to-end data product design, data contracts, and governance, while writing production code and setting high standards for quality and observability.

You will lead the pod’s engineering standards, collaborate with ML teams, and ensure data products meet SLAs/SLOs with robust CI/CD practices.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 6+ years building and operating production data pipelines and consumer-facing data models.
• Hands-on Python and SQL with ability to write/review code.
• Experience with Databricks or Spark-based lakehouse environments.
• Strong dimensional modeling experience (grain, keys, slowly changing dimensions).
• Experience with orchestration tools (Dagster, Airflow, or similar) and CI/CD.

Responsibilities

• Lead the design of data products end to end: ingestion, cleansing, conformance, modeling, and Gold layer.
• Own dimensional design and CD/BD alignment across pod’s products.
• Set where logic belongs (Silver vs Gold) and ensure consumer-facing quality.
• Lead code reviews, enforce testing and observable pipelines.
• Collaborate with ML engineering for training data sources and contracts.

Skills

Python

SQL

Dimensional modeling

Data pipelines

Leadership

Education

Bachelor’s degree in Computer Science/Information Systems/Engineering

Tools

Databricks

Delta Lake

Dagster

Airflow

Git

Azure DevOps

dbt

Job description

Protective is seeking a Lead Data Engineer to define technical direction for a data product pod on Voyager, our Databricks lakehouse on Azure. You will own end-to-end data product design, data contracts, and governance, while writing production code and setting high standards for quality and observability.

You will lead the pod’s engineering standards, collaborate with ML teams, and ensure data products meet SLAs/SLOs with robust CI/CD practices.