Senior Data Engineer: EDW & Delta Lake on Databricks

United States Digital Space LLC; United States; Hybrid; USD 120,000 - 170,000; Full time

Benefits offered by this job

Hybrid/remote work options

Excellent benefits package

Job summary

PANTHERx Rare Pharmacy seeks a Senior Data Engineer to own the EDW and core data pipelines on Databricks, implementing Bronze-Silver-Gold layers and event-driven ingestion. You’ll drive architecture, governance and reliability while mentoring engineers and partnering with QA and Data Governance.

This role supports a hybrid home/office work arrangement in the Pittsburgh area, with emphasis on scalable, low-latency data platforms and production-grade data services across the enterprise.

Qualifications

• 6+ years of progressive data engineering experience with production ownership.
• Hands-on Databricks experience in production: Delta Lake and medallion architecture.
• Advanced SQL with PySpark and Python to build complex transformations.
• Experience with Azure data services and CI/CD in Azure DevOps.

Responsibilities

• Design, build, and operate enterprise data warehouse pipelines in the Databricks medallion architecture.
• Own production systems, manage data model integrity and SLAs.
• Develop Delta Lake pipelines and event-driven ingestion patterns.
• Document decisions and maintain runbooks; mentor engineers.

Skills

Databricks

Delta Lake

Unity Catalog

PySpark

Python

SQL

Azure

Data Modeling

Documentation

Leadership/Mentoring

Education

Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent experience

Tools

Azure Databricks

Azure Data Lake Storage

Azure Data Factory

CI/CD in Azure DevOps

Job description

PANTHERx Rare Pharmacy seeks a Senior Data Engineer to own the EDW and core data pipelines on Databricks, implementing Bronze-Silver-Gold layers and event-driven ingestion. You’ll drive architecture, governance and reliability while mentoring engineers and partnering with QA and Data Governance.

This role supports a hybrid home/office work arrangement in the Pittsburgh area, with emphasis on scalable, low-latency data platforms and production-grade data services across the enterprise.