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Biomedical Data Engineer Jobs (NOW HIRING)

Data Systems/Solutions Engineer

Indianapolis, IN · Hybrid

$109K - $131K/yr

The Engineer applies modern software engineering and data engineering practices to ensure data ... Support integration and use of clinical and biomedical data standards (e.g., EHR data, HL7/FHIR ...

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Biomedical Data Engineer information

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How much do biomedical data engineer jobs pay per hour?

As of Jun 24, 2026, the average hourly pay for biomedical data engineer in the United States is $62.98, according to ZipRecruiter salary data. Most workers in this role earn between $53.61 and $70.91 per hour, depending on experience, location, and employer.

Can a biomedical engineer become a data scientist?

A biomedical engineer can become a data scientist by acquiring skills in programming, statistics, and machine learning, often through additional training or certifications. Their background in healthcare data and analytical thinking can be advantageous in transitioning to data science roles within biomedical or healthcare industries.

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.

How much do biomedical data scientists make in the US?

Biomedical data scientists in the US typically earn between $80,000 and $130,000 annually, depending on experience, education, and location. Entry-level positions may start lower, while those with advanced skills in data analysis, machine learning, and programming can earn higher salaries.

Can a biomedical engineer make 200k?

Biomedical data engineers can potentially earn $200,000 or more annually, especially with extensive experience, advanced skills in data analysis and programming, and work in high-demand sectors like medical device companies or research institutions. However, salaries vary based on location, education, certifications, and the complexity of projects handled.

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 engineers make $500,000?

Senior biomedical data engineers with extensive experience, advanced skills in data analysis, machine learning, and familiarity with healthcare data systems can reach salaries of $500,000 or more, especially in high-cost regions or with leadership roles. Achieving this level often requires advanced degrees, certifications, and a strong track record of impactful projects.

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.

More about Biomedical Data Engineer jobs
What cities are hiring for Biomedical Data Engineer jobs? Cities with the most Biomedical Data Engineer job openings:
What states have the most Biomedical Data Engineer jobs? States with the most job openings for Biomedical Data Engineer jobs include:
Infographic showing various Biomedical Data Engineer job openings in the United States as of June 2026, with employment types broken down into 11% Internship, and 89% Full Time. Highlights an 100% In-person job distribution, with an average salary of $131,001 per year, or $63 per hour.

Biomedical Engineering QA Lead - Remote

YO IT Consulting

Remote

Full-time

Posted 5 days ago


Job description

Job Summary:
YO IT Consulting is a fast-growing AI Data Services company delivering training data for major AI companies. They are seeking a Biomedical Engineering Quality Assurance Lead to oversee quality and consistency across biomedical engineering AI training projects, review AI-generated content, and ensure adherence to quality standards.
Responsibilities:
• Quality monitoring: Spot-check biomedical engineering items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
• Technical review: Evaluate AI-generated biomedical engineering explanations, medical-device reasoning, biomechanics calculations, biomaterials discussions, bioinstrumentation workflows, biosignal explanations, diagrams/descriptions, and problem-solving steps for correctness and clarity.
• Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and biomedical-engineering-specific review standards.
• Question handling: Respond to trainer/QA questions clearly and promptly, especially around engineering assumptions, units, formulas, biological context, device safety, regulatory considerations, standards references, and rubric interpretation.
• Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed.
• Documentation: Create and maintain biomedical engineering project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
• Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and biomedical-engineering-specific review requirements.
• Quality alignment: Ensure all trainers and QAs apply biomedical engineering guidelines consistently and understand updates as projects evolve.
• Risk and safety review: Flag unsafe, misleading, or overconfident biomedical engineering recommendations, especially where medical devices, patient safety, clinical workflows, biological systems, diagnostics, imaging, rehabilitation tools, or regulatory claims may be affected.
• Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for biomedical engineering AI training projects.
Qualifications:
Required:
• Bachelor’s or Master’s degree in Biomedical Engineering, Bioengineering, Medical Engineering, Biomechanical Engineering, Electrical Engineering with biomedical focus, Mechanical Engineering with biomedical focus, or a closely related field.
• Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear technical feedback in English.
• 3+ years of professional experience in biomedical engineering, medical devices, biomechanics, biomaterials, bioinstrumentation, clinical engineering, R&D, regulatory documentation, technical review, engineering education, or related workflows.
• Strong understanding of core biomedical engineering topics such as biomechanics, biomaterials, medical devices, bioinstrumentation, biosignals, imaging systems, physiological systems, tissue engineering, rehabilitation engineering, and biomedical data analysis.
• Ability to evaluate biomedical engineering content against detailed rubrics and identify issues such as incorrect assumptions, flawed calculations, missing units, unsafe recommendations, weak biological/clinical reasoning, hallucinated standards, regulatory overclaims, or incomplete explanations.
• Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, calibration tasks, and other quality documentation.
Preferred:
• Familiarity with common biomedical engineering tools or workflows such as MATLAB, Python, LabVIEW, SolidWorks, CAD/CAE tools, signal processing workflows, medical device documentation, ISO/FDA-related documentation, clinical engineering workflows, or biomedical data analysis tools.
• Experience leading or supporting remote teams of trainers, annotators, reviewers, engineers, technical writers, or QAs.
• Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
• Experience with AI training, data annotation, large language models, prompt/response evaluation, technical content QA, biomedical content QA, or rubric-based LLM evaluation.
Company:
Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) — including machine learning (ML), data analytics, automation, natural language processing (NLP), computer vision, and related technologies — to solve real-world problems, improve decision-making, automate repetitive tasks, and deliver intelligent solutions across industries. Founded in 2018, the company is headquartered in Abu Dhabi, Abu Dhabi Emirate, AE, , with a team of 51-200 employees. The company is currently Growth Stage.