Data Engineer

Location: South Bend, IN (Hybrid)

Compensation: $100,000 - $110,000

About The Role

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

Nice-to-Have

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

Key Responsibilities

Data Engineering & Platform Development

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

Data Architecture & Optimization

Support the design of a unified enterprise data model Optimize data processing performance and reliability Ensure data quality, validation, and integrity across pipelines

Collaboration & Strategy

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

#ZRCFSTECH #INOCT2026

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