Jobs / United States / Mastercard International Incorporated

Lead Data Engineer

Arlington, Virginia Posted today

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Skills this job asks for

SnowflakeAWSData engineeringAzureLeadershipCI/CDElectronic health recordsSparkSQLPythonGit

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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.
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.
What Mastercard International Incorporated paid sponsored hires in similar roles4 certified filings for “Data Engineer” (Data Scientists) in VA: $116k–$143k, median $127k.
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 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. 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 Mastercard International Incorporated paid sponsored hires in similar roles: 4 certified filings for “Data Engineer” (Data Scientists) in VA: $116k–$143k, median $127k. Most were filed at wage level II (75%) — 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

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 Lead Data Engineer Overview: Mastercard’s Data Commercialization Platform (DCP) team is seeking a Lead Data Engineer to design, build, and scale cloud-native data and Business Intelligence solutions across a modern multi-cloud data ecosystem. This role will focus heavily on Databricks, Snowflake, and AWS, building scalable data pipelines, analytics frameworks, and platform capabilities that support enterprise data products. You will also help drive a multi-cloud architecture across AWS and Azure, enabling secure and governed interoperability across platforms, compute engines, and cloud providers. The ideal candidate combines strong hands-on engineering expertise with technical leadership and can translate complex platform requirements into scalable, reliable, secure, and cost-effective solutions. This is a hybrid role based in Arlington, VA requiring three days per week onsite. Role: • Design and develop cloud-native data and BI solutions using Databricks and Snowflake on AWS. • Build scalable, high-performance data pipelines and analytics frameworks supporting enterprise data products. • Drive implementation of multi-cloud architectures across AWS and Azure, including Azure Databricks and ADLS Gen2. • Enable seamless integration and interoperability across Databricks, Snowflake, AWS services, and Azure services. • Build and maintain CI/CD pipelines, automation frameworks, and Infrastructure as Code for reliable data platform provisioning and deployment. • Implement secure and governed access patterns using RBAC, IAM, service principals, and enterprise identity integration. • Design reusable platform capabilities that enable data interoperability across multiple compute engines and cloud providers. • Establish engineering standards for development, testing, deployment, monitoring, documentation, and operational excellence. • Optimize data platforms and workloads for performance, scalability, reliability, resiliency, and cost efficiency. • Lead technical design reviews and influence architecture and platform engineering decisions. • Partner with Product, Architecture, Engineering, Data, and Business teams to translate complex requirements into scalable and sustainable technical solutions. • Provide technical leadership and mentorship to engineers while driving initiatives from design through implementation. All About You: • Deep hands-on experience as a Lead or Senior Data Engineer, designing and building enterprise-scale cloud data, analytics, and BI platforms. • Strong expertise with Databricks, Snowflake, and AWS, including AWS services such as S3, Glue, EMR, and IAM. • Advanced proficiency with Apache Spark/PySpark, Delta Lake, SQL, and Python for large-scale data processing and analytics. • Experience building scalable ETL/ELT pipelines, data integration frameworks, and distributed data solutions. • Experience designing multi-cloud data architectures and integrations across AWS and Azure; experience with Azure Databricks and ADLS Gen2 is a plus. • Strong experience with CI/CD, Infrastructure as Code, automation, Git/GitHub, and DevOps practices for data platforms. • Experience implementing enterprise security, governance, and access controls, including RBAC, IAM, service principals, data lineage, metadata

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Lead Data Engineer

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