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# Imaging Data Engineer

- **Company:** VEGA IMAGING INFORMATICS, LLC
- **Location:** United States (Remote available)
- **Salary:** $80,000.0 - $110,000.0
- **Contract:** Permanent contract
- **Skills:** Microsoft Excel, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon S3, Microsoft Azure, Big Data, Command-Line Interface, Cloud Computing, Cloud Storage, Computer Programming, Databases, Data Deduplication, Extract Transform Load (ETL), Data Manipulation Languages, Data Structures, Linux, Dicom, File Systems, File Transfer, Python (Programming Language), Machine Learning, Windows PowerShell, Software Tools, Standard Sql, SQL Databases, Data Processing, Google Cloud, Cloud Platform System, Containerization, Information Technology, Build Process, Data Management, Software Coding, Restful APIs, Data Pipelines, Docker
- **Published:** October 8, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=bcf7fa21f837a788

## About the Role

We're looking for someone who is technically strong, curious, resourceful, and comfortable taking on challenging data projects.

Required

 * Strong programming/scripting experience in Python, PowerShell, or a similar language.
 * Strong understanding of filesystems, databases, data structures, and data-processing workflows.
 * Experience working with large datasets and automating data-intensive processes.
 * Strong Excel/CSV/data manipulation skills.
 * Ability to troubleshoot problems independently and develop practical solutions.
 * Strong attention to detail. In medical imaging data, a single incorrect metadata field can matter.
 * Ability to work comfortably from the command line and automate tasks rather than performing repetitive work manually.
 * Strong organizational and documentation skills.

Highly Preferred

Experience with one or more of the following:

 * DICOM / medical imaging
 * Certified Imaging Informatics Profession (CIIP) certification
 * PACS or medical imaging systems
 * Radiology, cardiology, pathology, dental, or other clinical imaging data
 * Medical image de-identification
 * Python imaging/data libraries
 * SQL
 * AWS, Google Cloud, Azure, or other cloud platforms
 * Object storage such as S3 or GCS
 * Docker or other container technologies
 * REST APIs
 * PowerShell
 * Linux
 * ETL/ELT pipelines
 * Large-scale data migration
 * Data quality and validation frameworks
 * Machine learning or AI datasets, You may be a particularly strong fit if you:
 * Enjoy working with complex datasets.
 * Like understanding how things work at a low level.
 * Enjoy automation and eliminating repetitive manual processes.
 * Are comfortable learning technologies that you haven't used before.
 * Can move between Python, PowerShell, SQL, command-line tools, and cloud environments as needed.
 * Have an interest in medical imaging, healthcare, or AI.
 * Are equally comfortable writing code and troubleshooting a strange data problem.
 * Care about data quality and understand that "mostly correct" isn't good enough for healthcare data.
 * Enjoy working in a small, highly entrepreneurial environment where each team contributes in a variety of ways.

## Description

This is a highly hands-on role for someone who enjoys solving difficult data problems. You will work directly with massive collections of DICOM and other medical imaging files, develop automated data pipelines, troubleshoot imaging and metadata issues, and help transform raw clinical imaging into high-quality datasets that are ready for AI development.

What You'll Do

 * Build, maintain, and improve pipelines for ingesting, processing, organizing, validating, and exporting large medical imaging datasets.
 * Work extensively with DICOM files, including DICOM metadata, pixel data, medical reports, demographic data, and other patient/study information.
 * Develop automated workflows for de-identification and quality control of medical images and associated metadata.
 * Process and manage very large datasets containing millions of imaging studies and potentially terabytes or petabytes of data.
 * Utilize tools to identify, extract, transform, validate, and organize imaging data from complex folder structures and disparate source systems.
 * Automate repetitive data-management tasks using Python, PowerShell, SQL, APIs, and other scripting/engineering tools.
 * Develop processes to identify missing, corrupt, duplicated, inconsistent, or otherwise problematic imaging data.
 * Analyze and manipulate large datasets containing patient, study, series, accession, modality, demographic, and clinical metadata.
 * Work with cloud and object storage environments such as AWS S3, Google Cloud Storage, Azure, Backblaze B2, and similar platforms.
 * Work with imaging transfer technologies including DICOM, DICOMweb, PACS, cloud storage, secure file transfer, and large-scale data migration.
 * Build processes for dataset curation, including cohort selection, deduplication, date shifting, metadata normalization, and quality assurance.
 * Help develop internal tools that make it easier for our team to search, inspect, validate, and work with massive imaging datasets.
 * Investigate unusual imaging/data problems and develop practical solutions rather than simply escalating them.
 * Collaborate with data scientists, AI developers, imaging experts, and healthcare organizations to understand and solve data requirements.
 * Help establish repeatable, documented, and auditable processes for producing high-quality medical imaging datasets.