Senior Data Engineer

Mastercard is hiring a Senior Data Engineer. Level rates it ; you can apply on Mastercard.

Level's read on this job

On Level's scale, this data engineer role is Uses AI ●●○○: an ordinary role that requires AI tools.
Tools and skills the posting cites include Copilot, Databricks and Python.
Level classifies it as a senior role.
Level lists 967 other open roles at Mastercard.

AI in this role

Build and optimize scalable data platforms, pipelines, and systems that enable advanced analytics and machine learning.

CopilotDatabricksPythonSparkSQLAirflow

data-engineeringetldata-pipelinesdata-warehousingdistributed-systems

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 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.

Pay Ranges

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

How we rate this

Senior Data Engineer at Mastercard rates 40 out of 100 for how much of the daily work is AI. That makes it Uses AI (AI Level 2 of 4). The level is about AI in the job, not seniority.

Classification

Uses AI. An ordinary role that requires AI tools.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior Data Engineer is an open job at Mastercard.
Level rates this role AI Level 2 of 4: Uses AI.
The role is based in O'Fallon, Missouri.
The job was posted on September 15, 2026.
Seniority: senior.
Applications are handled by Mastercard. Apply on Mastercard

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Data EngineeringETLData PipelinesData WarehousingDistributed SystemsCopilotDatabricksPython

Also common in data engineer jobs at this level

Python Java Snowflake Generative AI Airflow Kafka

Pay

Typical data engineer job: $146k

This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs

Questions you could be asked

Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where etl was part of your work. What did you do?
Tell me about a project where data pipelines was part of your work. What did you do?
Tell me about a project where data warehousing was part of your work. What did you do?
Tell me about a project where distributed systems was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Data Engineering, ETL, Data Pipelines, Data Warehousing, and Distributed Systems. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Put the AI tool in a bullet point about what you did, not just in a skills list. This role treats it as a required part of the job.

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