Data Engineer

Job Description

Job Description

We are looking for a Data Engineer to help shape and expand a cloud-focused data environment that supports analytics, operational reporting, automation, and emerging AI use cases. Based in Brookfield, Wisconsin, this position works across technical and business teams to deliver dependable data solutions that improve access, accuracy, and usability. The role is ideal for someone who thrives on translating complex data needs into scalable engineering outcomes and values collaboration, problem-solving, and continuous improvement.

Responsibilities:
• Design, build, and maintain scalable data pipelines that move and transform information for analytics, reporting, and operational needs.
• Partner with business stakeholders, analysts, software developers, and leaders to understand data requirements and turn them into reliable engineering solutions.
• Develop and refine data models and platform architecture to support performance, flexibility, and long-term growth.
• Implement ETL processes that integrate data from multiple sources while improving consistency, completeness, and accessibility.
• Use Python and distributed data technologies such as Apache Spark and Hadoop to process large and complex datasets efficiently.
• Support streaming and event-driven data workflows using tools such as Apache Kafka where real-time data delivery is needed.
• Monitor data quality, troubleshoot pipeline issues, and optimize workflows to ensure dependable delivery and strong system performance.
• Contribute to ongoing enhancements of the data platform by identifying opportunities to improve scalability, automation, and engineering standards.• Experience in data engineering with a strong track record of building and supporting production data pipelines.
• Hands-on proficiency in Python for data processing, transformation, and workflow development.
• Experience working with Apache Spark to manage large-scale data workloads.
• Familiarity with Hadoop-based ecosystems and distributed data processing concepts.
• Practical knowledge of Apache Kafka or similar streaming technologies for real-time data movement.
• Strong understanding of ETL design, implementation, and optimization across varied data sources.
• Ability to collaborate effectively with cross-functional teams and translate business needs into technical solutions.