Jobs / United States / Mastercard International Incorporated
Data Engineer II
Mastercard International Incorporated · 🇺🇸 O'Fallon, Missouri
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 76 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 286 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 Mastercard International Incorporated paid sponsored hires in similar roles7 certified filings for “Data Engineer” (Data Scientists) in MO: $98k–$138k, median $119k. Most were filed at wage level IV (57%) — 4 lottery entries, ≈61% 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 — Mastercard International Incorporated
The US Department of Labor certified 76 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 286 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 Mastercard International Incorporated →
About the role
Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Data Engineer II Overview: Mastercard’s Enterprise Credit Risk (ECR) team is seeking a Data Engineer II to design, build, and maintain data platforms and products that support credit decisioning, risk analytics, regulatory reporting, and machine learning initiatives. In this role, you will work with large and complex datasets to develop scalable, reliable, and high-quality data solutions. You will collaborate with engineers, data scientists, risk analytics, and product partners to translate business needs into effective data products and pipelines. This is an opportunity for an engineer to deepen their data engineering expertise while contributing to modern cloud-based platforms and ECR's ongoing data modernization efforts. This is a hybrid role based in O’Fallon, MO, requiring three days per week onsite. Role: • Design, develop, test, and maintain scalable data pipelines, transformations, and datasets supporting ECR products and initiatives. • Build and optimize ETL/ELT workflows using technologies such as SQL, Python, Databricks, and Spark. • Develop and maintain curated data products that support reporting, analytics, credit decisioning, and other business use cases. • Partner with Product, Risk Analytics, Data Science, and Engineering teams to understand requirements and translate them into effective technical solutions. • Implement data validation, testing, and quality controls to ensure data accuracy, consistency, and reliability. • Support the deployment, monitoring, and ongoing operation of production data pipelines and workflows. • Investigate and troubleshoot data and pipeline issues, contributing to root cause analysis and resolution. • Participate in code reviews and follow established engineering standards, best practices, and development processes. • Contribute to the modernization of data platforms, including cloud migration and adoption of modern data engineering technologies. • Document data solutions, pipelines, data flows, and operational processes. • Identify opportunities to improve the performance, reliability, scalability, and efficiency of data solutions. All About You: • Experience as a Data Engineer or in a similar technical role, with a solid understanding of core data engineering concepts, methodologies, and best practices. • Experience designing, building, and maintaining ETL/ELT pipelines and data transformations. • Strong SQL skills, including the ability to write and optimize queries to retrieve, transform, and analyze large datasets efficiently. • Experience with Python or another programming language used for data processing and automation. • Experience working with relational databases, including Postgress, and an understanding of data modeling and database design. • Familiarity with cloud-based data platforms and modern data engineering technologies. • Familiarity with distributed data processing technologies such as Databricks, Apache Spark, or comparable platforms. • Understanding of data testing, validation, and quality practices to ensure accuracy and consistency across data pipelines. • Strong analytical and problem-solving skills, with the ability to troubleshoot complex data issues and develop effective solutions. • Ability to manage multiple tasks and priorities whi