Jobs Companies Mastercard Senior Data Engineer

Über diese Senior Data Engineer Stelle bei Mastercard

Mastercard · Hybrid · O'Fallon, Missouri

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 Foundry is seeking a Senior Data Engineer. In this role, you will take ownership of building and optimizing data platforms, pipelines, and systems that enable advanced analytics, machine learning, and business insights. You’ll collaborate closely with engineering, product, and analytics teams to deliver reliable, production-ready data solutions.
Mastercard Foundry is the innovation engine of Mastercard and a hub for new product development. We do this by driving product innovation in emerging technologies and interfaces while focusing on developing a point of view to enhance existing solutions and new use-cases. We also focus on building revenue generating ecosystems and flywheels that can be standalone in adjacent segments and markets. Examples of focus areas include Digital Assets/Stablecoins, Consumer value propositions, Digital payments, Payment Acceptance and Processing, and applications of Artificial Intelligence.

This is a hybrid role based in O’Fallon, MO, with an expectation of three days per week onsite.

Role:
• Design, build, and maintain scalable, reliable data platforms, pipelines, and data products that support analytics, machine learning, and business insights.
• Develop and optimize large-scale batch and streaming data pipelines using modern distributed data processing frameworks.
• Implement workflow orchestration and automation solutions to ensure reliable and efficient data movement and processing.
• Design and integrate data from multiple sources to create accessible, high-quality datasets for business and technical stakeholders.
• Build and maintain modern data lake and data warehousing solutions that support diverse analytical use cases.
• Define and implement scalable data models and database solutions that ensure performance, integrity, and usability.
• Apply data engineering best practices to improve system performance, scalability, resiliency, and maintainability.
• Ensure compliance with data security, governance, privacy, and regulatory requirements.
• Lead technical design discussions and contribute to architecture decisions across data platforms and services.
• Own end-to-end delivery across the SDLC, including requirements, design, development, testing, deployment, and support.
• Troubleshoot production issues, perform root cause analysis, and drive corrective and preventive actions.
• Collaborate with cross-functional teams while mentoring engineers and promoting engineering excellence and knowledge sharing.

All About You:
• Experience as a Data Engineer or in a similar role, with strong knowledge of data engineering concepts, methodologies, and modern data architectures.
• Strong hands-on experience with SQL, including writing and optimizing queries for large-scale data processing.
• Strong experience with relational databases, particularly Microsoft SQL Server and related technologies.
• Experience designing, implementing, and maintaining ETL/ELT pipelines and data integration solutions.
• Strong experience with distributed data processing and large-scale data platforms; experience with Databricks and Spark is a plus.
• Experience building and maintaining data lakes, data models, and scalable database solutions for analytics and reporting.
• Knowledge of workflow orchestration and automated end-to-end data pipelines.
• Understanding of data security, governance, compliance, and data quality practices, particularly in enterprise environments.
• Experience with cloud platforms such as AWS, Azure, or GCP and modern data engineering tools.
• Experience with event-driven or streaming architectures and exposure to machine learning or advanced analytics environments is a plus.
• Strong troubleshooting, root cause analysis, critical thinking, and problem-solving skills, with the ability to break down complex technical challenges.
• Ability to manage multiple projects and competing priorities while maintaining high standards for quality, accuracy, and delivery.
• Strong verbal and written communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
• Self-motivated and collaborative team player with the ability to influence technical decisions, mentor engineers, and demonstrate curiosity about emerging technologies and developer productivity tools such as GitHub Copilot.
• Bachelor's degree in a quantitative discipline such as Engineering, Mathematics, Finance, Business, or a related field. Equivalent practical experience may 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 [email protected] 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.

Pay Ranges

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

Bereit, sich bei Mastercard zu bewerben?
Bei Mastercard bewerben

Wie sich dieses Gehalt für Data Engineer vergleicht

Diese Stelle zahlt $149,500/yrim Einklang mit der üblichen Spanne für Data Engineer Stellen.

$96,721 dem Median $158,868 $243,750

Übliche Spanne $125,000–$199,138/yr, aus 1,642 vergleichbaren Data Engineer Anzeigen auf JobsRadar (Vergütung auf USD hochgerechnet). Gehaltseinblicke für Data Engineer ansehen →

Über Mastercard

Everyone wants easier ways to pay; we invent them. Checkout lines are slow; we speed them along. Merchants want more sales; we give them data and insights. People need financial access; we connect them. Corporate purchasing is complicated; we make it simple. Commuters are busy; we speed them on their way. Governments need greater efficiencies; we help create them. Small businesses are virtual; we give them access to a world of buyers. Retailers want to fight fraud; we provide the tools.

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