Data Engineer

We are looking for an experienced Data Engineer to join a team in Madison, Wisconsin, in a contract capacity with the potential for a permanent role. This position will focus on building and optimizing modern data solutions that support scientific and business decision-making, with particular relevance to bioinformatics and life sciences data. The ideal candidate brings deep expertise in cloud-based data engineering, strong hands-on experience with Databricks and Azure, and the ability to collaborate effectively with technical and non-technical partners.

Responsibilities:
• Design, build, and maintain scalable data pipelines and integration workflows that support reporting, analytics, and downstream scientific applications.
• Develop and optimize cloud-based data platforms using Databricks, Python, Spark, and Delta Lake to manage large and complex datasets efficiently.
• Create and enhance data models, database objects, and processing logic within relational database environments to improve reliability and performance.
• Implement data warehousing practices that enable trusted, organized, and accessible data for research and operational use.
• Work with biological, genomic, and other omics data to support analysis, interpretation, and delivery of usable datasets for life sciences teams.
• Partner with stakeholders across IT, research, and business functions to translate data needs into practical engineering solutions.
• Apply strong analytical thinking to troubleshoot data issues, refine processes, and ensure alignment with scientific requirements.
• Contribute within Agile delivery environments by participating in planning, iterative development, and cross-functional collaboration.

Qualifications:

• Bachelor’s degree in Computer Science, Information Systems, Bioinformatics, Computational Biology, or a closely related discipline; an advanced degree is a plus.
• At least 7 years of experience in data integration, reporting, and the design or operation of cloud-based data platforms.
• Advanced hands-on experience with Databricks technologies, including Python, Spark, and Delta Lake.
• Strong command of relational databases, including development of queries, stored procedures, and related database functions.
• Solid understanding of data warehousing principles and established best practices for managing enterprise data.
• Experience working within Microsoft Azure environments; familiarity with Microsoft Fabric is beneficial.
• Practical exposure to bioinformatics or life sciences data, such as genomic, sequence, omics, or phenotypic datasets, is strongly preferred.
• Legal authorization to work in the United States is required.

Compensation

$57.00-$66.00 Hourly

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