Jobs / United States / Medtronic INC

Medtronic INC

Data Engineer

Lafayette, Colorado, United States of America Posted today

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Sponsorship verdict

Sponsorship possible

One solid signal, not two. Worth applying, and worth asking about sponsorship early.

  • Employer is on a government sponsor recordThe US Department of Labor certified 193 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
  • What Medtronic INC paid sponsored hires in similar roles2 certified filings for “Senior Data Engineer - AWS” (Data Scientists) in CA: $151k–$159k, median $155k.
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
Employer is on a government sponsor record
The US Department of Labor certified 193 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
What Medtronic INC paid sponsored hires in similar roles
2 certified filings for “Senior Data Engineer - AWS” (Data Scientists) in CA: $151k–$159k, median $155k. Most were filed at wage level III (100%) — 3 lottery entries, ≈46% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.

About the role

We anticipate the application window for this opening will close on - 27 Oct 2026   Careers that change lives start here. Medtronic is a global leader in healthcare technology with a Mission to alleviate pain, restore health, and extend life. Our 95,000 employees work across more than 150 countries to put patients first — developing innovative medical technologies that improve the lives of 72+ million patients each year. Your unique talents will help shape the future of healthcare while building a career grounded in purpose, growth, and impact. A Day in the Life At Medtronic CST, we bring together innovative technologies that empower surgeons and improve outcomes in complex spine and cranial procedures. Check us out on LinkedIn: Medtronic CST Within the Research and Technology (R&T) organization, the team develops the data, infrastructure, and processes that enable advanced algorithms, as well as artificial intelligence (AI) and machine learning (ML) capabilities across future product portfolios. The function partners closely with systems engineering, software engineering, clinical, regulatory, marketing, and data science stakeholders to establish scalable data foundations that support algorithm development, validation, and product readiness.                     This role is responsible for building and managing the data foundations required to support advanced algorithms, as well as AI and ML development across surgical planning, navigation, and robotics programs. The Data Engineer will lead data acquisition, annotation operations, quality processes, and data governance activities while partnering with cross-functional teams to ensure data assets are scalable, compliant, traceable, and fit for algorithm development and validation. • Lead the activities of data creation and data acquisition; design and execute robust data collection strategies. • Manage annotation and labeling partners and clinical experts for data annotations to needed scale and quality. • Work closely with AI and Product Development teams to define the required data for development of state-of-the-art algorithms. • Contribute to data quality and integrity to ensure the database is well organized and easily accessible. • Maintain and improve data reliability and quality. • Utilize data development and management tools including AI tooling. • Work closely with algorithm developers, test engineers, and Legal and Regulatory departments to assess data compliance. • Work with external and internal providers to manage the R&D database. • Support engineers in R&D data acquisition needs, including designing data collection. • Coordinate with clinical teams on collection of data in clinical trials. • Help inform research and development  decisions with data-focused analytics and inputs. • Support other programs and initiatives as assigned. Primary Responsibilities • Lead data acquisition, curation, and preparation activities to support research and product development programs. • Design and implement data collection strategies, protocols, and workflows for clinical, laboratory, internal, and external data sources. • Manage internal and external annotation programs and partners to deliver high-quality labeled datasets at scale. • Establish and maintain data quality standards, validation processes, and governance practices to improve reliability, integrity, and traceability. • Partner with researchers, software engineers, and algorithm developers to define data requirements for artificial intelligence and machine learning initiatives. • Support database administration, organization, and accessibility of structured and unstructured datasets used across development programs. • Collaborate with Legal, Regulatory, and Clinical stakeholders to ensure datase

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