Jobs / United States / Abacus Insights INC
Engineering Manager (Data)
Abacus Insights INC · 🇺🇸 Nepal
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 10 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 3 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 Abacus Insights INC paid sponsored hires in similar roles1 certified filing for “Business Analyst Manager – Data Distribution Team” (Computer and Information Systems Managers) in GA: $155k–$155k, median $155k. Most were filed at wage level II (100%) — 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 — Abacus Insights INC
The US Department of Labor certified 10 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 3 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 Abacus Insights INC →
About the role
About Us Abacus Insights is transforming how data and AI work for health plans. Our mission is simple: make healthcare data usable, so the people responsible for care and cost decisions can act faster, with confidence. As the AI and Data Platform for Payer Intelligence, we help health plans break down data silos to create a single, trusted data foundation. That foundation powers better decisions—so plans can improve outcomes, reduce waste, and deliver better experiences for members and providers alike. Backed by $100M from top investors, we're tackling big challenges in an industry that's ready for change. Our platform enables GenAI use cases by delivering clean, connected, and reliable healthcare data to support automation, prioritization, and decision workflows—and it's why we are leading the way. Our innovation begins with people. We are bold, curious, and collaborative—because the best ideas come from working together. We embrace the thoughtful use of AI and automation to drive innovation and efficiency, and we look for individuals who are curious and adaptable—those excited to leverage emerging technologies to enhance how we work—while keeping human insight, connection, and our clients at the center of every decision. Ready to make an impact? Join us and let's build the future together. About the Role The Engineering Manager is a key leader within our Technical Implementation organization, leading a globally distributed team of approximately 10–12 data engineering professionals. This role bridges client delivery, technical execution, and people leadership, with a strong focus on successful client implementations and scalable, high-quality data engineering practices. This hands-on leadership role combines technical depth with operational discipline. The manager will guide feature delivery teams, partner with cross-functional stakeholders, and ensure reliable execution across complex healthcare data use cases, including ETL workflows, data mapping, and clinical data integration. Your day to day • Lead Client Implementations: Manage end-to-end client implementations, ensuring timely, high-quality delivery aligned with client expectations. • Guide Data Engineering Execution: Provide technical leadership across ETL, data mapping, and integration workflows, promoting consistency and best practices. • Optimize Interoperability Workflows: Work with stakeholders to improve CMS Interoperability and related implementation processes. • Manage Global Teams: Partner with offshore and distributed teams to coordinate delivery, align priorities, and maintain operational rigor. • Coach and Develop Talent: Mentor engineers and new hires while building a collaborative, performance-driven team culture. • Own Operational Execution: Support delivery management, resource planning, and prioritization with delivery and product teams. • Set and Track Performance Metrics: Define team success measures, monitor progress, and drive continuous improvement. • Encourage Innovation: Promote practical adoption of tools, technologies, and approaches that improve scalability, quality, and efficiency. What you bring to the team • 7+ years of experience in data engineering roles, including client‑facing implementations. • Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field. • Demonstrated experience leading and mentoring technical teams. • Strong hands‑on experience designing and supporting ETL workflows and complex data integrations. Proficiency with Python and PySpark for data processing and transformation. • Strong ability to write, optimize, and manage complex queries across large datasets. • Experience working with AWS‑based architectures; familiarity with Databricks and Snowflake. • Practica