Data Engineer

eNGINE; Pittsburgh (Allegheny County); On-site; USD 110,000 - 160,000; Full time

Job summary

eNGINE is seeking Senior Data Engineers to own and evolve our enterprise data warehouse on the Databricks platform, from raw ingestion to clean, trusted tables used by business analytics.

You will own data models, pipeline reliability, and quality checks, while helping build automation and event-driven architecture to move away from old batch patterns. Documentation is emphasized to ensure platform longevity.

Qualifications

• Hands-on data engineering with ownership of a warehouse or large pipelines with SLAs.
• Deep Databricks experience: Delta Lake, medallion architecture, Unity Catalog.
• Strong data modeling with conformance and harmonization.
• Advanced SQL plus PySpark and Python.
• Experience with Azure Data Factory, Data Lake Storage, and CI/CD.
• Ability to walk into a complex, loosely documented system and make sense of it.
• Excellent communication with technical and business stakeholders.

Responsibilities

• Own specific domains within the warehouse, including data models and pipeline reliability.
• Implement quality checks to ensure trustworthy data.
• Contribute to automation and event-driven architecture to modernize pipelines.
• Design and build pipelines across Bronze, Silver, and Gold layers.
• Write transformation and harmonization logic turning raw data into usable datasets.
• Develop Gold-layer tables for reporting and analytics.
• Maintain comprehensive documentation to prevent knowledge silos.

Skills

Data engineering

Databricks

SQL

PySpark

Python

Azure data stack

CI/CD

Data modeling

Stakeholder communication

Tools

Delta Lake

Unity Catalog

Azure Data Factory

Azure Data Lake Storage

Kafka

Job description

eNGINE builds Technical Teams. We are a Solutions and Placement firm shaped by decades of interaction with Technical professionals. Our inspiration is continuous learning and engagement with the markets we serve, the talent we represent, and the teams we build. Our Consulting Workforce is encouraged to enjoy career fulfillment in the form of challenging projects, schedule flexibility, and paid training/certifications. Successful outcomes start and finish with eNGINE.

eNGINE is hiring multiple Senior Data Engineers to help own and evolve our enterprise data warehouse. You'll be responsible for how data moves through our Databricks platform — from raw ingestion all the way through to the clean, trusted tables the business relies on every day.

This isn't a role where you're handed a ticket and told what to build. You'll own specific domains within the warehouse outright — the data models, the pipeline reliability, the quality checks that keep everything trustworthy. You'll also help build out the automation and event-driven architecture that moves us away from older, slower batch patterns.

Day to day, you'll design and build pipelines across our Bronze, Silver, and Gold layers, write the transformation and harmonization logic that turns raw data into something usable, and build out the Gold-layer tables that feed our reporting and analytics work. You'll also spend real time on documentation — not as an afterthought, but because we don't want any part of this platform to depend on one person's memory.

What we're looking for

• Several years of hands-on data engineering experience, including real ownership of a warehouse or large-scale pipelines with actual SLAs to hit
• Deep, practical experience with Databricks — Delta Lake, medallion architecture, Unity Catalog
• Strong data modeling background, especially conformance and harmonization logic
• Advanced SQL along with solid PySpark and Python skills
• Experience with Azure's data stack — Data Factory, Data Lake Storage, and Azure DevOps for CI/CD
• Ability to walk into a complex, loosely documented system and make sense of it
• Comfortable communicating directly with technical and business stakeholders alike

Nice to have

• Background in healthcare, specialty pharmacy, or another regulated industry
• Experience with event-driven ingestion tools like Event Hubs or Kafka
• Familiarity with data contract standards or observability platforms like Monte Carlo
• Exposure to enterprise data catalog tools such as Atlan or Collibra
• A track record of mentoring engineers and setting technical standards without needing a formal title to back it up