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# DEX Engineer

- **Company:** Robert Half
- **Location:** Cincinnati, OH, United States
- **Contract:** Temporary contract
- **Skills:** Business Analytics Applications, Computer Programming, Data Architecture, Information Engineering, Extract Transform Load (ETL), Data Systems, Distributed Computing Environment, Distributed Data Store, Apache Hadoop, Python (Programming Language), Data Streaming, Data Processing, Apache Spark, Real Time Data, Apache Kafka, Data Pipelines
- **Published:** August 28, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3367767410&tx=YT404CYZ&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Strong programming ability in Python for data engineering and automation tasks.
 * Working knowledge of Apache Hadoop and distributed data ecosystems.
 * Experience using Apache Kafka for event-driven or streaming data solutions.
 * Proven background in ETL design, development, and support.
 * Ability to troubleshoot data pipeline issues and improve performance in complex environments.
 * Strong collaboration and communication skills in cross-functional technical settings. Technology Doesn't Change the World, People Do., All applicants applying for U.S. job openings must be legally authorized to work in the United States. Benefits are available to contract/temporary professionals, including medical, vision, dental, and life and disability insurance. Hired contract/temporary professionals are also eligible to enroll in our company 401(k) plan. Visit roberthalf.gobenefits.net for more information.

## Description

* Build and optimize large-scale data pipelines using Python and Apache Spark to support reliable data processing.
 * Develop ETL workflows that collect, transform, and deliver data from multiple source systems into analytical platforms.
 * Work with Hadoop-based environments to manage distributed data processing and storage effectively.
 * Implement and support Kafka-driven streaming solutions for near real-time data ingestion and integration.
 * Monitor pipeline performance, troubleshoot data issues, and improve processing efficiency across engineering workflows.
 * Collaborate with technical teams to understand data needs and translate them into scalable engineering solutions.
 * Maintain data quality standards by validating outputs, resolving inconsistencies, and supporting dependable data availability.
 * Contribute to ongoing enhancements of data architecture, including updates to existing platforms and operational processes. Requirements - Hands-on experience with Apache Spark for large-volume data processing.


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