Senior Data Engineer - Indiana
Summary
Senior Data Engineer at Radcube supporting a client-facing data and AI engagement in Indianapolis (onsite/hybrid, local candidates only). Day to day: designing and maintaining data pipelines, processing solutions and platforms using modern data/AI technologies like Databricks and NVIDIA, while translating business needs into technical solutions.
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