Data Engineer
Location: South Bend, IN (Hybrid)
Salary: Up to $125,000 (Mid-Level) | Up to $150,000 (Senior-Level)
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
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Strong experience with Azure data services (Azure Data Factory, Azure SQL, Synapse, etc.)
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Hands-on experience with Databricks
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Strong proficiency in Python and Spark
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Experience developing and optimizing ETL/ELT pipelines
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Background working with legacy Microsoft tools such as SSIS and SSRS
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Deep understanding of data modeling, transformation logic, and pipeline architecture
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Experience consolidating data into centralized or cloud-based platforms
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Strong SQL skills
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Ability to troubleshoot performance issues and optimize large-scale datasets
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Strong communication skills and ability to collaborate cross-functionally
Nice-to-Have
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Experience supporting enterprise BI/reporting environments
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Exposure to ERP, operational, or transactional data systems
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Experience in manufacturing, agriculture, supply chain, or similar industries
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Familiarity with data governance and best practices
Key Responsibilities
Data Engineering & Platform Development
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Design, build, and maintain scalable data pipelines using Databricks, Azure, Python, and Spark
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Migrate and modernize legacy SSIS/SSRS workflows into the centralized data platform
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Develop robust ETL/ELT processes to integrate data from multiple enterprise systems
Data Architecture & Optimization
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Support the design of a unified enterprise data model
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Optimize data processing performance and reliability
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Ensure data quality, validation, and integrity across pipelines
Collaboration & Strategy
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Partner with BI, analytics, and business teams to support enterprise reporting needs
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Contribute to data standards, governance, and architectural best practices
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Support the organization’s transition to a modern, centralized data ecosystem