Databricks Data Engineer

The Databricks Data Engineer will be part of the Data Services team and help transform the delivery of data driven insights at scale. In this role, they will design and engineer robust data pipelines using technologies like Databricks, Azure Data Factory, Apache Spark, and Delta Lake. This role will work hands on crafting healthcare data solutions - processing massive healthcare datasets, optimizing performance, and ensuring our data is accurate, secure, and accessible when it matters most.

Knowledge/Skills/Abilities/Expectations:

• Excellent problem-solving and analytical skills
• Strong oral and written communication abilities
• Self-motivated with ability to adapt to new technologies quickly
• Team player with ability to work independently
• Detail-oriented with strong organizational skills
• Ability to manage multiple priorities and meet deadlines
• Experience communicating technical concepts to non-technical stakeholders

Technical Skills:

• Databricks Platform:
  • Expert-level knowledge of Databricks Workspace, clusters, and notebooks
  • Delta Lake implementation and optimization
  • Unity Catalog for data governance and cataloging
  • Databricks SQL and SQL Analytics
  • Databricks Workflows, Delta Live Tables, and job orchestration
  • Delta Live Tables (DLT) for pipeline orchestration and data quality
• Programming & Development:
  • Advanced Python programming (PySpark, pandas, NumPy)
  • Advanced SQL (query optimization, performance tuning)
  • Scala programming (preferred)
  • Git version control and collaborative development
• Cloud Technologies:
  • Azure Databricks
  • Cloud storage services (ADLS Gen2, Azure Blob Storage)
  • Azure Data Factory for pipeline orchestration and integration
  • Experience designing and managing Azure Data Factory pipelines, triggers, and linked services
  • Infrastructure as Code (Terraform)
• Business Intelligence & Analytics:
  • Experience with BI tools (Power BI, SSRS)
  • Data warehousing and data modeling concepts
  • SQL Server, including SSIS (Integration Services)
  • MLflow for ML lifecycle management (plus)
• Preferred Additional Skills
  • Experience with complex data modeling including dimensional modeling, star/snowflake schemas
  • Experience with medallion architecture (bronze/silver/gold layers)
  • Data quality and validation framework implementation
  • CI/CD pipeline development for data workflows (Azure DevOps)
  • Performance tuning and cost optimization
  • DataOps and DevOps practices

Education/Experience:

• Bachelor's degree in Computer Science, Information Technology or related field
• 5+ years of progressive experience in data engineering, analytics, or software development
• 3+ years of hands-on experience with Databricks platform
• Strong experience with Apache Spark and PySpark
• Healthcare IT or healthcare data experience preferred

Licenses/Certification:

• Databricks Certified Data Engineer Associate (strongly preferred)
• Databricks Certified Data Engineer Professional
• Databricks Lakehouse Fundamentals
• Azure Data Engineer Associate (DP-203)
• Apache Spark certifications