Mastercard · O'Fallon, Missouri, US

Senior Data Engineer

OpenFull-timePay not stated

Open — Mastercard has a posting for this job. Posted 27 Oct 2026.

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Posted 27 Oct 2026 · Full-time · Pay not stated

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About this job

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

Senior Data Engineer

Overview:
Mastercard’s Data Collection & Engineering (DC&E) organization is seeking a Senior Data Engineer to
play a critical role in designing, building, and scaling Mastercard's next-generation data platforms and analytical ecosystems.
In this role, you will develop high-performance, cloud-enabled data pipelines that power Mastercard's enterprise data warehouse and Lakehouse environments. Your work will enable advanced analytics, business intelligence, regulatory reporting, and data-driven decision making across the organization.
This role offers a unique opportunity to solve large-scale data engineering challenges while working with cutting-edge big data technologies and contribute to a modern cloud transformation program supporting global payment processing platforms.
The Data Collection & Engineering (DC&E) organization powers the global economy by enabling secure, seamless, and intelligent payments across the world. Behind every transaction is a sophisticated technology ecosystem that processes billions of payment events with speed, resilience, and precision.
This is a hybrid position based in O’Fallon, MO, requiring three days per week onsite.

Role:
• Design, develop, test, and deploy secure, scalable, high-performance, and resilient data pipelines using Apache Spark, Java/Scala, Hadoop, and cloud-native object storage platforms.
• Build and maintain batch and near-real-time data processing frameworks capable of supporting petabyte-scale workloads and demanding enterprise data requirements.
• Develop reusable engineering components, frameworks, and design patterns that accelerate data product delivery while maintaining enterprise architecture and engineering standards.
• Design and implement “build once, run anywhere” architectures that enable seamless deployment across on-premises and public cloud environments without requiring code changes.
• Implement enterprise data capabilities including data lineage, metadata management, data cataloging, data quality, monitoring, and observability across the data ecosystem.
• Collaborate with architects and platform teams to establish scalable architecture patterns, distributed computing practices, and engineering standards, while driving adoption of modern Lakehouse architectures.
• Contribute to cloud modernization initiatives by migrating legacy ETL, data warehouse, and analytics workloads from on-premises environments to cloud-native architectures using services such as Amazon S3, EMR, and AWS Glue.
• Lead end-to-end engineering activities, including requirements analysis, solution design, coding, testing, deployment, production support, and continuous optimization.
• Partner with product owners, analysts, architects, and business stakeholders to translate requirements into high-quality, scalable solutions and deliver committed outcomes within established timelines.
• Troubleshoot complex production incidents, perform root cause analysis, and implement sustainable remediation strategies while ensuring compliance with Mastercard’s security, quality, and operational governance standards.
• Mentor and guide engineers through code reviews, technical coaching, knowledge sharing, and best practices, while identifying opportunities to improve performance, automation, monitoring, and engineering efficiency.

All About You:
• Hands-on experience as a Data Engineer or Senior Data Engineer delivering enterprise-scale Data Warehouse, Data Lake, or Data Lakehouse solutions.
• Proven experience delivering multiple end-to-end data engineering initiatives within large-scale distributed computing environments.
• Hands-on experience migrating ETL/ELT, data warehouse, and analytics workloads from on-premises platforms to cloud-native architectures.
• Strong development experience with Apache Spark, Scala and/or Java, Hadoop ecosystem technologies, and cloud object storage platforms.
• Experience building orchestration and workflow solutions using Apache Airflow, Apache NiFi, or comparable enterprise scheduling and workflow frameworks.
• Strong SQL expertise and experience working with relational and NoSQL databases, such as Oracle, SQL Server, Cassandra, and DynamoDB.
• Working knowledge of cloud platforms, preferably AWS, including Amazon S3, EMR, AWS Glue, and other cloud-native data services.
• Strong understanding of security, privacy, regulatory, and compliance requirements associated with sensitive financial and customer data.
• Proven ability to lead complex technical initiatives across multiple teams and influence engineering direction without direct authority.
• Demonstrated ability to mentor engineers and elevate technical capability, including providing design guidance, knowledge sharing, and constructive feedback.
• Excellent communication and stakeholder management skills, with the ability to clearly articulate technical concepts, trade-offs, risks, dependencies, and recommendations to both technical and business audiences.
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related STEM discipline. Equivalent practical experience will also be considered.

Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.

Corporate Security Responsibility

All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

  • Abide by Mastercard’s security policies and practices;
  • Ensure the confidentiality and integrity of the information being accessed;
  • Report any suspected information security violation or breach, and
  • Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations. THIS POSTING RELECTS ONE OR MORE CURRENT VACANCIES ON OUR TEAM, AND MASTERCARD INTENDS TO FILL THIS POSITION BY 12/30/2026. If the fill date has passed, Mastercard intends to fill this position as soon as possible.

Pay Ranges

O'Fallon, Missouri: $115,000 - $184,000 USD

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  • Other posting · Req OFallon-Missouri · Posted 27 Oct 2026

    Pay not stated

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  • Other posting · Req OFallon-Missouri · Posted 27 Oct 2026

    Pay not stated

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  • Other posting · Req OFallon-Missouri · Posted 3 Sep 2026

    Pay not stated

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If the main posting closes, the newest of these takes its place and this page stays open.

Not this job's pay

What do Corporate – Information Technology jobs in Missouri pay?

Talentify has no pay figure for this posting. The lines below are about Corporate – Information Technology jobs on Talentify in Missouri as a group, computed by Talentify's job index across their postings. They are not the pay for this job.

Of the 143 Corporate – Information Technology jobs on Talentify in Missouri, 16 list pay per year.

Taking the midpoint of each listed range, the middle half pay 88,000–113,763 USD per year and the median is 102,750 USD per year.

11 of these 16 name no currency; they are counted as USD because the jobs are in the United States.

Pay as employers listed it, not adjusted or verified. Updated 2026-11-06.

Computed on 2026-11-06 from the pay in 16 listings.

Also open

Also open at Mastercard

Mastercard's other jobs that have a page here. Each page says open or closed for itself.

Same job, other employers

Data Engineer jobs in Missouri at other employers

Pages on Talentify for this job in Missouri, at employers other than Mastercard. Each page says open or closed for itself.

This page remembers. 4 postings recorded.

4 postings recorded.computed from 3 events, 2026-10-28 to 2026-10-28.