Data Engineer II

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.

Data Engineer II

Mastercard Services Technology is seeking a Data Engineer II to contribute to the data management aspects of client engagements for Test & Learn and other Services products. In this role, you will develop robust data pipelines, implement scalable data solutions, and collaborate with cross‑functional teams. Engineers work in small, flexible teams. Every team member contributes to designing, building, and testing features.

The Test & Learn team aims to build industry‑leading business experimentation software that brings sophisticated analytic techniques to business users around the world. We are rapidly expanding our product offerings and innovating on how we deliver Test & Learn solutions to our clients.

This is a hybrid role based in Arlington, VA, with an expectation of three days per week onsite.

• Support the design, implementation, and maintenance of enterprise ETL processes for data platforms, for a global client base.
• Assist in the data delivery process, working alongside Data Engineers and Analysts to support on‑time, accurate, high‑value, and robust data solutions across multiple clients and industry sectors.
• Use SQL and other database technologies to optimize data processing. Develop scalable and efficient code to reduce the time required to handle large data sets.
• Learn and apply industry best practices, including version control, code reviews, and data validation, to ensure quality in data processes.
• Participate in efforts to design streamlined processes to automate routine data tasks.
• Build trust‑based working relationships with peers and clients across local and global teams. Collaborate with senior and peer engineers on multiple projects in parallel.
• Comply with all Mastercard internal policies and adhere to external regulations.

• Experience as a Data Engineer or in a similar role, with a strong understanding of data engineering concepts and methodologies, including data modeling and database design to support scalable data solutions.
• Strong knowledge of writing and optimizing SQL queries to retrieve, manipulate, and analyze data efficiently.
• Experience with Relational Databases (RDBMS), with strong hands‑on expertise in Microsoft SQL Server and related technologies.
• Familiarity with ETL frameworks and the ability to design, implement, and maintain data pipelines.
• Experience with Databricks and Spark is a plus, but not required.
• Demonstrate curiosity about emerging developer productivity tools (e.g., Git Hub Copilot); prior experience is not required, but a willingness to learn and experiment is highly valued.
• Demonstrate skills in the ability to innovate, think critically and disaggregate problems.
• Able to handle tasks on multiple projects and differing project priorities.
• Ability to analyze and troubleshoot data issues and provide solutions with minimal supervision.
• Basic knowledge of testing and validating data to ensure accuracy and consistency in data pipelines.
• Excellent verbal and written communication skills, with the ability to articulate complex ideas clearly and concisely to both technical and non‑technical stakeholders.
• Bachelor's degree in a quantitative discipline such as Engineering, Mathematics, Finance, Business, or a related field. Equivalent practical experience may also be considered.

This role is not eligible for Mastercard's work authorization sponsorship. Candidates must be authorized to work in the United States now and in the future without employer sponsorship.

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Arlington, Virginia:  -  USD

Mastercard is a merit‑based, inclusive, equal opportunity employer that considers applicants without regard to…