Skip to main content
Tallo logoTallo logo

Find Jobs

Find Jobs Near You – Available Work in Your Location

Skip to job details

Back to Results

Apply for this opportunity

To apply for this job, you'll continue to an external website or email application.

Robert Half

Data Engineer

Review key factors to help you decide if the role fits your goals.
Pay Growth
?
out of 5
Not enough data
Not enough info to score pay or growth
Job Security
?
out of 5
Not enough data
Calculating job security score...
Total Score
81
out of 100
Average of individual scores

Were these scores useful?

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.