Jobs / United States / Omada Health INC
Senior Software Engineer, Data Engineering
Omada Health INC · 🇺🇸 Remote, USA · Remote
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 7 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest May 2026) — the step every H-1B hire needs first. USCIS also records 1 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 Omada Health INC paid sponsored hires in similar roles1 certified filing for “Senor Applied AI Engineer” (Software Developers) in NY: $189k–$189k, median $189k. 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 — Omada Health INC
The US Department of Labor certified 7 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest May 2026) — the step every H-1B hire needs first. USCIS also records 1 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 Omada Health INC →
About the role
Omada Health is on a mission to bend the curve of chronic disease. Job overview: We are dedicated to leveraging data to drive strategic decision-making and operational efficiency. Our team is passionate about harnessing the power of data to solve complex problems and deliver impactful insights. We are seeking a highly skilled and motivated Data Engineer to join our team. The ideal candidate will be responsible for designing, building, and maintaining robust data architectures and engineering data models and pipelines. This role will play a critical part in ensuring the integrity, scalability, and performance of our data processing and products. Key Responsibilities: • Data Architecture: Design, develop, and implement scalable, secure, and efficient data solutions that meet the needs of the organization. • Data Modeling: Create and maintain logical and physical data models to support business intelligence, analytics, and reporting requirements. • Pipeline Engineering: Design, build, and optimize ETL (Extract, Transform, Load) processes and data pipelines to ensure smooth and efficient data flow from various sources. • Data Integration: Integrate diverse data sources, including APIs, databases, and third-party data, into a unified data platform. • Performance Optimization: Monitor and optimize the performance of data systems and pipelines to ensure low latency and high throughput. • Data Quality and Governance: Implement data quality checks, validation processes, and governance frameworks to ensure the accuracy and reliability of data. • Collaboration: Partner closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet their needs. • Documentation: Maintain comprehensive documentation of data architectures, models, and pipelines for ongoing maintenance and knowledge sharing. • Training: You'll train and collaborate with teammates effectively in data engineering best practices • Technical Influence/Leadership: Recommends policy changes and establishes department-wide procedures. Uses extensive experience and knowledge to resolve complex problems. • Monitor and manage production environment to deliver data within defined SLAs How you can make an impact: • You’ll evaluate, benchmark, and improve the scalability, robustness, and performance of our data platform and applications • You'll make significant contributions to the architecture and design of our data processing platform • You’ll implement scalable, fault tolerant, and accurate ETLs frameworks. • You’ll gather and process raw data at scale from diverse sources • You’ll collaborate with product management, data scientists, analysts, and other engineers on technical vision, design, and planning • You’ll implement and maintain a high level of data quality monitoring in our analytics & ML ecosystem • You’ll train and collaborate with teammates effectively in data engineering best practices • You will be responsible for leading, documenting, and collaborating across teams for technical projects. You will love this job if you: • You are passionate about building data-driven systems to enable Data Scientist, Data Analysts and AI/ML Engineers. • You want to make a difference to empower digital healthcare through Data-driven decision making. • You would like to learn how to build scalable, performant and reliable data pipelines. About you: Experience: • 5+ years of experience building, maintaining, and orchestrating scalable data pipelines. • 3+ years of experience as a data engineer developing or maintaining integration with software such as Airflow or any Python-based data pipeline codebase. • Experience applying a variety of integration patterns for different use cases. • Experience in