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# Data Engineer

- **Company:** MMM Companies LLC
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Data Analysis, Automation of Tests, Configuration Management, Databases, Continuous Integration, Data Architecture, Information Engineering, Data Files, Data Integration, Extract Transform Load (ETL), Data Warehousing, DevOps, Python (Programming Language), SAP ERP, Power BI, SAP HANA, SQL Databases, Snowflake, Data Layers, Data Lakes, Deployment Automation, Data Management, Software Version Control, Data Pipelines, Databricks
- **Published:** November 12, 2026
- **Apply:** https://www.careerbuilder.com/job-details/data-engineer-south-bend-in--9c40d476-9a65-465d-a9a0-33ae5b346c1a

## About the Role

Data Management, Database Extract Transform and Load (ETL), Data Sets, Data Modeling, Product Support, Data Lake, Systems Administration/Management, Data Warehousing, Data Analysis, Source Code/Configuration Management (SCM), * Bachelor's degree or higher (completed and verified prior to start)

 * 5+ years of experience in data engineering, data warehouse development, or analytics platform support.
 * Experience with SQL, Python, ETL/ELT development, data modeling, and data quality practices.
 * Databricks experience preferred, including notebook development, data engineering workflows, or Lakehouse architecture.
 * SAP HANA & SAP ERP knowledge helpful.
 * Experience with data platforms and tools such as Snowflake, AWS, Power BI, or similar technologies.

Additional qualifications that could help you succeed even further in this role include:

 * Strong communication and collaboration skills
 * Excellent stakeholder management skills
 * Ability to work effectively in cross-functional teams

## Description

As a Data Engineer, you will have the opportunity to tap into your curiosity and collaborate with some of the most innovative people around the world. Here, you will make an impact by:

 * Design, develop, and maintain data pipelines, ETL/ELT workflows, and data integration solutions.
 * Build and support trusted data products, including curated datasets, reusable data assets, semantic layers, and analytics-ready data models.
 * Support data lake, data warehouse, and analytics platform configuration, optimization, and operations.
 * Apply DevOps practices, including CI/CD, version control, automated testing, and deployment automation for data engineering solutions.

Monitor data quality, pipeline performance, platform reliability, and production support processes.