Data Engineer II

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

Level's read on this job

On Level's scale, this data engineer role is Works on AI ●●●○: the daily work is on AI products, without building the model.
Some of the work can be done remotely, according to the posting.
The posting mentions Databricks, Python and SQL among its tools and skills.
Level classes it as a mid-level role.
Mastercard has 1,000+ other open roles on Level.

AI in this role

Data Engineer II to design and maintain scalable data platforms, pipelines, and products supporting machine learning and credit risk analytics.

databrickspythonsqlspark

data-engineeringetlmachine-learningdata-pipelines

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 while working effectively in a fast-paced environment.
• Ability to work independently while collaborating effectively across cross-functional and Agile teams.
• A continuous improvement mindset, with the ability to think critically, innovate, and identify opportunities to enhance data solutions.
• Strong verbal and written communication skills, with the ability to clearly communicate technical concepts to both technical and non-technical stakeholders.
• 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 11/29/2026. If the fill date has passed, Mastercard intends to fill this position as soon as possible.

Pay Ranges

O'Fallon, Missouri: $92,000 - $147,000 USD

How we rate this

Data Engineer II at Mastercard rates 60 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● 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

Data Engineer II is an open job at Mastercard.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in O'Fallon, Missouri and is marked remote.
The job was posted on September 10, 2026.
Seniority: mid.
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 EngineeringETLMachine learningData PipelinesDatabricksPythonSQLSpark

Also common in data engineer jobs at this level

AWS Airflow Azure Scala Snowflake Google Cloud

Pay

Typical data engineer job: $149k

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 machine learning 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?
Walk me through how you've used Databricks in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Data Engineering, ETL, Machine learning, Data Pipelines, and Databricks. 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.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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