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Robert Half

Data Engineer

Robert Half
Brookfield, WI $100k - $130k/yr Full time Posted 4d ago
Big Data Bigdata Data Data Analysis Data Architecture Data Engineer Data Integration Data Pipeline Data Pipelines Data Platform Data Processing Data Warehouse Database ETL Hadoop Informatica Information Technology (IT) Kafka Spark Streaming Data
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Job Description

Brookfield, WI (onsite) with an annual salary range of USD 100,000 - 130,000. This Data Engineer role focuses on developing a cloud-forward data environment that supports analytics, reporting, automation, and emerging AI use cases, with collaboration across technical and business teams.

At Robert Half, you will help build scalable, dependable pipelines and platform solutions that keep data accessible, consistent, and ready for production use.

Benefits for contract/temporary professionals include medical, vision, dental, and life and disability insurance, along with 401(k) plan eligibility for hired contract/temporary professionals.

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 translate 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 along with distributed data technologies such as Apache Spark and Hadoop to process large and complex datasets efficiently.
  • Support streaming and event-driven workflows using Apache Kafka when real-time delivery is required.
  • Monitor data quality, troubleshoot pipeline issues, and optimize workflows to ensure dependable delivery and strong system performance.
  • Identify opportunities to improve scalability, automation, and engineering standards across the data platform.
  • Bring hands-on experience building and supporting production data pipelines, with a strong track record of delivery.

Requirements

  • Hands-on proficiency in Python for data processing, transformation, and workflow development.
  • Experience working with Apache Spark for 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 across cross-functional teams and translate business needs into technical solutions.

Technologies

  • Python
  • Apache Spark
  • Hadoop
  • Apache Kafka

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