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# Data Engineer

- **Company:** ConsultNet
- **Location:** Salt Lake City, UT, United States
- **Salary:** $93,600.0 - $114,400.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Cloud Computing, Data Validation, Data Files, Data Integration, Extract Transform Load (ETL), Relational Databases, Database Queries, Interoperability, Python (Programming Language), Machine Learning, Systems Development Life Cycle, Regression Testing, Cloud Platform System, Data Ingestion, Health Level Seven International, Data Pipelines, Programming Languages
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/data-engineer-salt-lake-city-ut--0053075e-221f-48b1-b9f9-d108805dcf13

## About the Role

Cloud Computing, Use Cases, Artificial Intelligence (AI), Healthcare, Data Analysis, Scalable System Development, Data Sets, Process Improvement, Data Modeling, Data Quality, * Experience building and supporting ETL/ELT or data-ingestion pipelines.

 * Strong SQL skills and experience working with relational databases.
 * Experience integrating data from multiple systems and managing changing source schemas.
 * Experience with data validation, data quality, and testing practices.
 * Ability to translate architecture and business requirements into scalable technical solutions., * Healthcare data experience.
 * Familiarity with healthcare data standards, record normalization, or interoperability concepts.
 * Experience with Python or other data-engineering programming languages.
 * Experience supporting cloud-based data platforms or downstream analytics environments.
 * Experience preparing datasets for advanced analytics, machine learning, or AI applications.

## Description

We are seeking a Data Engineer to help modernize the ingestion and harmonization of healthcare data from multiple sources. This role will build reliable, scalable pipelines that prepare data for analytics, research, cloud enablement, and AI-focused use cases., * Design, build, and maintain data-ingestion pipelines from multiple source systems.

 * Harmonize and standardize records from varied datasets and formats.
 * Improve current ingestion processes to make them more efficient, accurate, repeatable, and scalable.
 * Build resilient pipelines that can accommodate source-data changes, including added, removed, or revised fields.
 * Collaborate with data architects to implement data models and standards.
 * Support the creation of well-structured datasets for research, analytics, and cloud-based consumption.
 * Develop automated data-quality, validation, and monitoring processes.
 * Participate in unit and regression testing of data pipelines and datasets.