[Hiring] Data Engineer @Hillenbrand

Role Description

The Data Engineer will design, build, and optimize scalable data pipelines and curated data products within a modern Lakehouse architecture (Databricks). This role is responsible for delivering high-quality, business-ready datasets (gold layer) that power enterprise analytics and Power BI reporting. The ideal candidate has deep Databricks experience, strong data modeling skills, and a focus on building reliable, testable, and governed data solutions. Exposure to AI-driven development or AI agents is a plus.

Work You’ll Do

• Data Engineering & Pipeline Development
  • Design, develop, and maintain scalable data pipelines using Databricks and Delta Lake
  • Build and manage transformations across bronze, silver, and gold layers
  • Optimize processing for performance, reliability, and cost
  • Integrate data from ERP, CRM, APIs, and other enterprise systems
• Data Modeling & Business Logic
  • Develop gold-layer datasets aligned to standardized business definitions
  • Translate business requirements into reusable data models
  • Ensure consistency of core metrics across reporting
  • Align Databricks outputs with Power BI semantic models
• Data Quality, Testing & Reliability
  • Implement automated data quality checks and validation rules
  • Build testable, production-ready pipelines
  • Support impact analysis using lineage tools
  • Participate in CI/CD and deployment processes
• Performance Optimization & Operations
  • Monitor and optimize pipeline performance
  • Troubleshoot issues across environments
  • Ensure data consistency between dev, test, and prod
  • Support high-volume data workloads
• AI & Automation (Preferred)
  • Use AI-assisted tools for development (e.g., Copilot, Databricks Agents)
  • Explore AI agents for testing, lineage analysis, and optimization
  • Contribute to AI-driven engineering practices
• Collaboration & Stakeholder Engagement
  • Partner with BI and business teams
  • Support governance and cataloging efforts
  • Document data models and pipelines

Qualifications

• Bachelor’s degree in relevant field
• 8+ years data engineering experience
• Strong Databricks, Spark, Delta Lake experience
• SQL and Python proficiency
• Experience with Power BI or similar tools

Requirements

• Azure Data Factory, Synapse, or Data Lake experience
• DevOps and CI/CD experience
• AI agents or AI-assisted development exposure
• Experience in large, complex enterprise environments