Jobs / United States / Abbott Laboratories
Principal Data Engineer
Abbott Laboratories · 🇺🇸 United States > Madison : 1 Exact Lane
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 73 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. USCIS also records 28 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- 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. 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 Abbott Laboratories paid sponsored hires in similar roles3 certified filings for “STAFF SOFTWARE ENGINEER” (Software Developers) in TX: $135k–$158k, median $143k. Most were filed at wage level II (33%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
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.
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Sponsor Radar — Abbott Laboratories
The US Department of Labor certified 73 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. USCIS also records 28 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Abbott Laboratories →
About the role
Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 122,000 colleagues serve people in more than 160 countries. JOB DESCRIPTION: Position Overview The Principal Data Engineer (IC) is a senior individual contributor and the accountable technical leader for assigned cross-domain initiatives and enterprise data engineering capabilities. The role owns integrated technical direction and technical outcomes for work spanning multiple data domains, defines and stewards enterprise engineering standards and reference architectures, and drives convergence where duplicated or inconsistent solutions create enterprise cost, risk, or operational burden. The role advises on scope, sequencing, capacity, dependencies, and technical debt, but does not independently commit domain resources or business delivery dates. This position has no people-management responsibility. Enterprise Data operates a domain-aligned model built on Databricks and Unity Catalog. Working with Domain Leaders, Staff Engineers, Platform Engineering, and partner organizations, the role converts ambiguous enterprise needs into executable architecture and carries the most complex or highest-risk work through validation and production. The role remains hands-on through prototyping, reference implementations, critical-path development, design and code review, and production problem solving. This role is based in Madison, WI. Relocation assistance may be available for qualified candidates. Essential Duties Include, but are not limited to, the following: Cross-domain technical leadership and delivery • Own the technical outcome of assigned cross-domain initiatives from initial ambiguity through production and lifecycle support. • Convert enterprise needs into integrated architecture and executable technical plans, decomposing complex work into deliverable increments across domains. • Coordinate technical execution across domain Staff Engineers and partner teams, identifying dependencies and architectural risks, and escalating decisions requiring business or delivery authority. • Remain hands-on through prototypes, reference implementations, critical-path development, technical validation, and production problem solving. Enterprise architecture and standards • Define, steward, and evolve enterprise data engineering standards, patterns, and reference architectures, and drive convergence where inconsistent or duplicative implementations create enterprise cost, risk, or operational burden. • Lead architecture for assigned enterprise capabilities, including semantic and metrics layers, canonical data models, batch, API, event-driven, and streaming patterns, and governed data products supporting analytics, machine learning, and AI. • Establish enterprise data-contract standards covering schemas, service expectations, compatibility, breaking-change policy, and producer-consumer responsibilities, and partner with Platform Engineering to convert recurring cross-domain needs into shared capabilities. Technical leadership and mentorship • Lead enterprise design and code reviews for high-complexity or cross-domain work, and coach and mentor Staff and Senior Engineers across domains without formal people authority. • Communicate architecture and technical tradeoffs clearly to engineering, business, and executive stakeholders, and build reusable guidance that increases engineering consistency across Enterprise Data. Operational excellence, security, and efficiency • Evaluate architecture tradeoffs across reliability, scalability, performance, secu