Sponsorship verdict
Sponsorship possible
One solid signal, not two. Worth applying, and worth asking about sponsorship early.
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✓
Employer is on a government sponsor recordThe US Department of Labor certified 191 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.
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The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
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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.
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✓
What CVS Pharmacy INC paid sponsored hires in similar roles3 certified filings for “Manager, Data Engineer” (Data Scientists) in GA: $110k–$162k, median $110k.
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✓
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 191 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 CVS Pharmacy INC paid sponsored hires in similar roles
- 3 certified filings for “Manager, Data Engineer” (Data Scientists) in GA: $110k–$162k, median $110k. Most were filed at wage level II (67%) — 2 lottery entries, ≈31% 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’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time.
A Brief Overview
Leads and actively contributes to a team that builds the systems and AI-enabled platforms used to process, store, and serve data across the enterprise. This is a player coach role: roughly 50% of the time is spent hands-on in design, code, and architecture, with the remainder devoted to people leadership, cross-functional partnership, and strategy. The Senior Manager owns the growth, performance, and delivery of the team, partners closely with product, data science, and business teams, and turns emerging ideas into production-grade solutions.
Position Summary
The Senior Manager, Data Engineering & AI is both a people leader and a technical leader who leads from the front. This person manages a team of data and software engineers (employees and contractors), owns their development, performance, and delivery, and stays close to the work by committing approximately 50% of their time to hands on engineering, including prototyping, building core components, setting patterns, and solving the hardest technical problems alongside the team.
The role sits at the intersection of engineering, product, data science, and the business. The Senior Manager works with product managers to shape roadmaps, with data scientists to move models from experiment to production, and with business stakeholders to ensure data and AI investments deliver measurable outcomes. The ideal candidate combines deep full stack and data engineering expertise, strong software engineering fundamentals, and first principles thinking with a genuine commitment to building people and relationships. Experience in healthcare and contact center analytics engineering is highly valued.
What You Will Do
People Management & Team Leadership
• Manages a team of software engineers and data engineers, including hiring, onboarding, goal setting, performance management, career development, and retention.
• Provides regular coaching, feedback, and recognition, and addresses performance concerns directly and constructively.
• Mentors engineers, identifies skill gaps, and provides training and growth opportunities to strengthen team capabilities.
• Leads a blended team of employees and contractors, ensuring clear expectations, accountability, and a cohesive team culture.
• Plans team capacity and priorities, balancing delivery commitments, technical debt, and individual growth.
• Models a growth mindset, encouraging experimentation, learning, and continuous improvement.
Hands-On Engineering & Technical Leadership
• Dedicates approximately 50% of time to hands-on work, including designing, coding, prototyping, and troubleshooting data pipelines, services, and AI enabled applications.
• Sets the bar for engineering quality by authoring reference implementations, establishing patterns, and tackling the most complex technical challenges alongside the team.
• Performs code reviews and enforces coding standards, based on company and industry requirements, across the development teams.
• Applies first principles thinking and sound design fundamentals to simplify complex problems and avoid unnecessary complexity.
Strategy & Architecture
• Defines strategy for the full software development lifecycle, utilizing emerging technologies and key data design principles in developing data pipelines, interfaces, and architecture to support
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