Data Engineer – Databricks & Lakehouse (Power BI Environment)

Position Summary:

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 Youll 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

Basic Qualifications:

Bachelors 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

Preferred Qualifications:

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

Who we are:

Mold-Masters () is a leading global supplier of hot runners controllers auxiliary injection and co-injection systems. We design manufacture distribute sell and service highly engineered and customized plastic processing equipment that caters to every market. Mold-Masters is a business unit of Hillenbrand.

Hillenbrand () is a global industrial company that provides highly engineered mission-critical processing equipment and solutions to customers in over 100 countries around the world. Our portfolio is composed of leading industrial brands that serve large attractive end markets including durable plastics food and recycling. Guided by our Purpose Shape What Matters For Tomorrow we pursue excellence collaboration and innovation to consistently shape solutions that best serve our associates customers communities and other stakeholders.

EEO: The policy of Hillenbrand Inc. is to extend opportunities to qualified applicants and employees on an equal basis regardless of an individuals age race color sex religion national origin disability sexual orientation gender identity/expression or veteran status. Additionally Hillenbrand Inc. and our operating companies are committed to being an Equal Employment Opportunity (EEO) Employer and offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment email us your email please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying. At Hillenbrand everyone is welcome to apply and Shape What Matters for Tomorrow.