Data Engineer
Listed on 2026-03-01
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IT/Tech
Data Engineer, Data Analyst, Data Warehousing, Data Science Manager
Location:
South Bend, IN (Hybrid)
Salary:
Up to $125,000 (Mid-Level) | Up to $150,000 (Senior-Level)
An organization in South Bend, IN is seeking a Data Engineer to play a critical role in building and optimizing a centralized enterprise data platform. This position is ideal for a hands‑on engineer who thrives in modern Azure environments and has strong experience designing scalable data pipelines using Databricks, Python, and Spark.
As the organization consolidates data into a single, unified platform, this role will focus on engineering robust ETL/ELT processes, modernizing legacy data workflows, and ensuring reliable, high‑performance data delivery across the enterprise.
This is a highly visible role working closely with analytics, IT, and business stakeholders to support enterprise‑wide reporting, operational intelligence, and long‑term data strategy.
What We’re Looking For Must‑Have Skills- Strong experience with Azure data services (Azure Data Factory, Azure SQL, Synapse, etc.)
- Hands‑on experience with Databricks
- Strong proficiency in Python and Spark
- Experience developing and optimizing ETL/ELT pipelines
- Background working with legacy Microsoft tools such as SSIS and SSRS
- Deep understanding of data modeling, transformation logic, and pipeline architecture
- Experience consolidating data into centralized or cloud‑based platforms
- Strong SQL skills
- Ability to troubleshoot performance issues and optimize large‑scale datasets
- Strong communication skills and ability to collaborate cross‑functionally
- Experience supporting enterprise BI/reporting environments
- Exposure to ERP, operational, or transactional data systems
- Experience in manufacturing, agriculture, supply chain, or similar industries
- Familiarity with data governance and best practices
- Design, build, and maintain scalable data pipelines using Databricks, Azure, Python, and Spark
- Migrate and modernize legacy SSIS/SSRS workflows into the centralized data platform
- Develop robust ETL/ELT processes to integrate data from multiple enterprise systems
- Support the design of a unified enterprise data model
- Optimize data processing performance and reliability
- Ensure data quality, validation, and integrity across pipelines
- Partner with BI, analytics, and business teams to support enterprise reporting needs
- Contribute to data standards, governance, and architectural best practices
- Support the organization’s transition to a modern, centralized data ecosystem
to apply online
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