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# Data Engineer

- **Company:** Robert Half
- **Location:** Salt Lake City, UT, United States
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Amazon Web Services, Cloud Database, Data Architecture, Information Engineering, Data Transformation, Data Systems, Dimensional Modeling, Python (Programming Language), SQL Databases, Cloud Platform System, Pyspark, Data Pipelines
- **Published:** July 18, 2026
- **Apply:** https://www.dice.com/job-detail/93317e24-5cc0-4714-924b-31c4964a443c

## About the Role

5+ years of experience in data engineering or a closely related field.

Proficiency with SQL and Python for developing and maintaining data solutions.

Hands-on experience with AWS technologies in a data-focused environment.

Strong understanding of dimensional modeling concepts, including practical use of the Kimball methodology.

Experience using dbt to build, organize, or manage data transformations.

Ability to work with cross-functional teams to deliver reliable and business-aligned data products.

Familiarity with PySpark is beneficial, though not required.

Exposure to cloud data infrastructure is a plus., 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

We are looking for a Data Engineer to help design and enhance data solutions that support reliable reporting and analytics in Salt Lake City, Utah. This role focuses on building scalable data pipelines, shaping well-structured warehouse models, and improving the quality and usability of enterprise data assets. The ideal candidate brings strong experience with SQL, Python, AWS technologies, and dimensional modeling principles grounded in the Kimball methodology., Build and maintain data pipelines that ingest, transform, and prepare information for downstream analytics and business use.
Design warehouse structures using Kimball-based dimensional modeling practices to support clear, consistent reporting.
Develop and optimize SQL- and Python-driven data workflows with an emphasis on scalability, performance, and maintainability.
Partner with analysts, engineers, and business stakeholders to translate data needs into practical engineering solutions.
Create and manage data transformation logic using dbt to improve testing, documentation, and deployment consistency.
Support cloud-based data platforms in an AWS environment and contribute to ongoing improvements in data architecture.
Monitor data quality and troubleshoot pipeline issues to ensure dependable delivery of curated datasets.
Contribute to modern data engineering practices, including tools such as PySpark when needed for larger-scale processing.


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