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# Data Engineer

- **Company:** Trans Ova Genetics
- **Location:** Madison, WI, United States
- **Contract:** Permanent contract
- **Skills:** Training Data, Artificial Intelligence, Data Analysis, Microsoft Azure, Information Systems, Databases, Information Engineering, Data Files, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Systems, Data Warehousing, Python (Programming Language), Microsoft Software, Microsoft SQL Server, Reliability Engineering, SQL Databases, SQL Server Reporting Services, SQL Server Integration Services, Data Streaming, Transact-SQL, Enterprise Software Applications, Cloud Platform System, Apache Spark, Microsoft Fabric, Data Lakes, Information Technology, Machine Learning Operations, Data Pipelines, Databricks
- **Published:** October 29, 2026
- **Apply:** https://www.careerbuilder.com/job-details/data-engineer-madison-wi--c3d498b9-6176-4226-a320-fb6ff37469fc

## About the Role

Training Data Sets, International Business, Artificial Intelligence (AI), Microsoft Product Family, Performance Management, Data Warehousing, Data Quality, Reliability Engineering, Database Extract Transform and Load (ETL), Data Sets, * Bachelor's degree in Computer Science, Information Systems, or a related field.

 * Strong hands-on experience with Databricks, including Python, Spark, and Delta Lake.
 * Strong SQL Server and data warehousing experience, including T-SQL.
 * Experience with SSIS and SSRS.
 * Experience with Microsoft Azure; Microsoft Fabric is a plus.
 * Experience using AI-assisted development tools as part of the engineering workflow.
 * Strong analytical, problem-solving, communication, and collaboration skills.

## Description

VAS, a URUS Group company, is looking for a Data Engineer to help design, build, and improve the data solutions that support our global business. Working primarily in Databricks, you'll develop and maintain pipelines and datasets that power reporting, analytics, and AI/ML workloads.

This role works across both modern and established data technologies, with a focus on improving performance, reliability, data quality, and scalability. We're looking for someone with strong data engineering fundamentals, hands-on Databricks experience, and a solid understanding of data warehousing and Microsoft-based data environments.

Responsibilities

 * Design, build, and maintain scalable ETL/ELT pipelines and datasets in Databricks using Python, Spark, and SQL.
 * Develop and support batch and streaming data architectures for reporting, analytics, and AI/ML workloads.
 * Troubleshoot and optimize Databricks and existing data integration processes for performance, reliability, and data latency.
 * Support and enhance existing SQL Server, SSIS, and SSRS solutions while contributing to ongoing platform modernization.
 * Implement data quality checks, validation, cleansing, and data warehousing best practices across data pipelines and reporting environments.
 * Integrate Databricks with enterprise applications, databases, and other data sources.
 * Partner with business users, analysts, and IT teams to translate reporting and data needs into scalable technical solutions.
 * Contribute to continuous improvement through emerging data engineering practices, AI-assisted development tools, documentation, and ongoing learning