Data Engineer
ConsultNet
Salt Lake City, UT, United States
8 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
$93,600.0 - $114,400.0
Working hours
Regular working hours
Job source
Tech stack
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
+7 more
Systems Development Life Cycle
Regression Testing
Cloud Platform System
Data Ingestion
Health Level Seven International
Data Pipelines
Programming Languages
Job 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.
Requirements
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.
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