Data Engineer, Mishawaka

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

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

Click here to apply online