Senior Data Engineer - Indiana

Key Responsibilities

• Design, build, and scale data pipelines on Databricks and AWS.
  
• Develop ETL/ELT solutions using Spark, PySpark, and SQL.
  
• Implement Delta Lake, Lakehouse, Unity Catalog, and Databricks Workflows.
  
• Work with AWS data services such as S3, Glue, Lambda, Redshift, and IAM.
  
• Build batch and streaming ingestion with data quality and governance controls.
  
• Apply CI/CD practices and optimize pipeline performance, cost, and reliability.
  
• Engage business and technical stakeholders directly and translate requirements into solutions.
  
• Contribute to data architecture and solution design discussions.
  
• Identify opportunities where data and AI can address additional business needs.
  
• Contribute to the growth of the overall engagement.
  

Requirements

Required Qualifications

• Strong hands on data engineering background.
  
• Python, PySpark/Spark, and SQL.
  
• Databricks, including Delta Lake and Lakehouse.
  
• Strong hands on experience with AWS data services.
  
• ETL/ELT pipeline development and data modeling.
  
• Batch and streaming ingestion, data quality and governance, CI/CD.
  
• Ability to engage stakeholders independently, not only work from technical tickets.
  
• Excellent communication and stakeholder management skills.
  
• Must be local to Indianapolis, IN and able to work onsite.
  

Preferred Experience

• Unity Catalog, MLflow, Medallion Architecture
  
• Databricks certification
  
• Azure
  
• NVIDIA ecosystem exposure
  
• GenAI and ML pipelines
  
• Regulated healthcare or pharma experience (pharma preferred, not mandatory)
  
• Experience identifying additional technology or business opportunities