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Biomedical Data Engineer Jobs in Minnesota (NOW HIRING)

Sapsol Technologies Inc

Program Engineer

Rochester, MN · On-site

While hands-on work in sequence development and data workflows is expected, the role does not ... B.S. or M.S. in Electrical Engineering, Biomedical Engineering, Physics, Computer Science, or ...

Elucent Medical

Systems Test Engineer

Eden Prairie, MN · On-site

$65K - $75K/yr

Use scripts, Python-based tools, automation, and data-analysis workflows to support testing ... Bachelor's degree in Engineering, Biomedical Engineering, Electrical Engineering, Mechanical ...

Tactile Medical

Senior Quality Engineer

Minneapolis, MN · On-site

$92K - $125K/yr

Bachelor level degree in Engineering (Mechanical, Material Science or Biomedical) or related ... review, analyze, summarize, and interpret data; draw conclusions and make appropriate ...

Nucleus RadioPharma

Quality Engineer

Rochester, MN · On-site

$100K - $130K/yr

Track and trend quality data to identify recurring issues and opportunities for improvement ... Bachelor's degree in engineering (e.g., Chemical, Biomedical, Mechanical, Electrical), Chemistry ...

Elucent Medical, Inc.

Senior R&D Engineer

Eden Prairie, MN · On-site

$125K - $160K/yr

Conduct hands-on engineering studies, testing, and data analysis to validate new sensing, signal ... Required: BS in electrical engineering, physics, biomedical engineering, or related technical field;

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Biomedical Data Engineer information

What are the key skills and qualifications needed to thrive as a Biomedical Data Engineer, and why are they important?

To thrive as a Biomedical Data Engineer, you need strong programming skills (e.g., Python, R), a background in biomedical sciences or bioinformatics, and experience with data modeling and analysis. Familiarity with big data frameworks, cloud platforms, and tools like SQL, Hadoop, and machine learning libraries, as well as relevant certifications, is commonly required. Excellent problem-solving abilities, attention to detail, and effective collaboration with cross-functional teams help you stand out in this role. These skills enable accurate analysis and integration of complex biomedical data, supporting critical healthcare research and innovation.

What are some common challenges faced by Biomedical Data Engineers when integrating clinical data from multiple sources?

Biomedical Data Engineers often encounter challenges related to data heterogeneity when integrating clinical information from diverse sources such as electronic health records, medical imaging systems, and genomic databases. These sources may use different formats, standards, and terminologies, making data cleaning and normalization a complex task. Additionally, ensuring patient privacy and compliance with healthcare regulations adds another layer of complexity. Collaborating with clinicians, data scientists, and IT teams is essential to address these challenges and ensure data is usable for research and decision-making.

What is a Biomedical Data Engineer?

A Biomedical Data Engineer is a professional who designs, develops, and maintains systems for collecting, storing, and analyzing biomedical data. They work at the intersection of healthcare and technology, collaborating with researchers, clinicians, and IT specialists to ensure that medical data is accessible, accurate, and secure. Their work supports medical research, diagnostics, and the development of healthcare solutions by leveraging large datasets, machine learning, and advanced analytics. Biomedical Data Engineers often use programming languages, database management, and data processing tools to handle complex health data from various sources.

What is the difference between Biomedical Data Engineer vs Biomedical Data Analyst?

AspectBiomedical Data EngineerBiomedical Data Analyst
Required CredentialsBachelor's or Master's in Bioinformatics, Computer Science, or related fields; experience with data engineering toolsBachelor's or Master's in Biology, Bioinformatics, or related fields; proficiency in data analysis and visualization
Work EnvironmentDevelops data pipelines, manages databases, and ensures data infrastructure for research and healthcareAnalyzes datasets, creates reports, and interprets data for research or clinical decision-making
Employer & Industry UsageResearch institutions, biotech companies, healthcare providersHospitals, research labs, biotech firms, healthcare organizations

While both roles work with biomedical data, Biomedical Data Engineers focus on building and maintaining data infrastructure, whereas Biomedical Data Analysts interpret and analyze data to support research and clinical decisions.

What are popular job titles related to Biomedical Data Engineer jobs in Minnesota? For Biomedical Data Engineer jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Biomedical Data Engineer jobs in Minnesota look for? The top searched job categories for Biomedical Data Engineer jobs in Minnesota are:
What cities in Minnesota are hiring for Biomedical Data Engineer jobs? Cities in Minnesota with the most Biomedical Data Engineer job openings:
Biomedical Data Engineer jobs near you
Infographic showing various Biomedical Data Engineer job openings in Minnesota as of July 2026, with employment types broken down into 3% Internship, 1% As Needed, 82% Full Time, 13% Part Time, and 1% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.
Medical Engineer

Medical Engineer

Sapsol Technologies Inc

Rochester, MN

Contractor

Re-posted 15 days ago

Job description

Role Summary

This role supports the development, integration, and validation of advanced MRI methods across two research workstreams:

  • Oscillating Gradient Diffusion (OGSE/OGD) in collaboration with Vanderbilt University, and
  • FLORETbased UTE imaging (nonCartesian) in collaboration with Cincinnati Children's Hospital.

The engineer will coordinate program execution while contributing technically to pulse sequence implementation, image reconstruction and software refinement, and data processing within the Philips MRI research environment. The emphasis is on program oversight, technical coordination, and collaborative execution, rather than independent subjectmatter leadership in diffusion MRI or FLORET.

Note: This role focuses on technical engagement and delivery. It does not include clinical trial operations or regulatory ownership.

Core Responsibilities

A) Technical Development - Pulse Sequence (OGSE/OGD)

  • Refine and extend existing OGSE pulse sequence code in the Philips research environment.
  • Implement additional features, improve robustness, and ensure correct sequence functionality.
  • Support deployment and onscanner integration on Philips MRI systems.
  • Contribute to related data processing and image reconstruction workflows when required.

B) Image Reconstruction & Software Development (FLORET / NonCartesian)

  • Implement and validate nonCartesian MRI reconstruction pipelines (including those supporting FLORET UTE acquisitions).
  • Support software deployment and integration of reconstruction tools within Philips research systems.
  • Refine reconstruction workflows, add new features, and improve system interfaces and usability.
  • Perform data validation and quality checks; evaluate reconstruction stability and artifact behavior.

C) Experimental Collaboration & Validation

  • Coordinate experiment planning with Vanderbilt researchers, Cincinnati Children's teams, and clinical MRI staff.
  • Support execution of scanner experiments as needed.
  • Assist with validation of OGSE and FLORET acquisition outputs through systematic testing and comparative analysis.
  • Prepare technical validation summaries/reports and ensure outputs align with program deliverables and milestones.
  • Document results, assumptions, and change histories with strong discipline.

Qualifications

Required

  • Strong familiarity with vendorspecific MRI pulse sequence programming (preferably Philips research environments).
  • Solid foundations in MRI reconstruction, including nonCartesian methods, and software engineering.
  • Handson experience with C++ / Python / MATLAB for algorithm and tooling development.
  • Ability to collaborate effectively across industry and academic partners; clear written and verbal communication.
  • Proven ability to operate under hardware constraints and in structured, sprintbased execution models.

Preferred

  • Master's or PhD in MRI Physics, Biomedical Engineering, Medical Physics, Electrical Engineering, Computer Science, or related field.
  • Experience with Philips MRI research environments (e.g., research interfaces, integration workflows).
  • Exposure to OGSE/OGD diffusion methods and/or FLORET UTE imaging (deep expertise not required).
  • Experience with MRI data processing, QA/QC, and validation workflows.

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