Data Engineer - Remote

Sentara is hiring a Data Engineer!

This is a fully remote position.

Overview

We are looking for a Data Engineer to support a modern data platform built on Databricks. This role will focus on building scalable data pipelines, supporting a metadata‑driven ingestion framework, and ensuring data quality and governance are embedded into the platform.

Key Responsibilities

• Develop and maintain data pipelines using PySpark and Databricks
• Work within a metadata‑driven ingestion framework to onboard new datasets
• Implement data quality checks and validation rules within pipelines
• Support ingestion from file‑based sources and ingestion tools (e.g., Fivetran)
• Handle schema changes, incremental loads, and file processing patterns
• Contribute to data governance practices including tagging, metadata, and lineage
• Troubleshoot and resolve pipeline failures and performance issues
• Collaborate with architects and stakeholders on data onboarding and requirements
• Follow and contribute to coding standards, reusable components, and best practices

Education

• Experience in lieu of a Bachelor’s Degree
• 3+ years of relevant experience with a degree
• 5+ years of relevant experience without a degree

Certification/Licensure

• No specific certification or licensure requirements

Experience

• Required to 3 to 5 years of relevant experience
• Hands‑on experience with PySpark and Databricks
• Strong SQL skills
• Experience building ETL/ELT data pipelines
• Understanding of Delta Lake concepts (merge, schema evolution, partitions)
• Familiarity with cloud platforms (Azure preferred)
• Basic experience with Git and version control
• Exposure to data catalog or governance tools (e.g., DataHub)
• Experience with Fivetran or similar ingestion tools
• Understanding of data quality and validation concepts
• Experience working with metadata‑driven frameworks
• Strong problem‑solving and debugging skills
• Ability to work in a structured, framework‑driven environment
• Focus on data quality, not just pipeline execution
• Willingness to learn and adapt in a fast‑evolving data ecosystem