Senior Data Engineer - Data & AI Platform

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 - Data & AI Platform

Senior Data Engineer – Data & AI Platform
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Who is Mastercard?

Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data, advanced technology, and strong partnerships, we help individuals, businesses, and governments realize their greatest potential.
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About Business & Market Insights (B&MI)

Business & Market Insights (B&MI) is Mastercard’s data, analytics, and intelligence organization, responsible for transforming vast, global data assets into actionable insights and decision-support products. B&MI builds platforms and solutions that embed advanced analytics, AI, and scalable data pipelines directly into customer workflows—enabling smarter decisions and measurable business outcomes.
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Overview

The Data & AI Foundations team builds scalable, enterprise-ready platforms that provide the data and AI infrastructure underpinning Mastercard’s analytics and insights products.

This is a platform engineering role. We build reusable services, standardized patterns, and automation that enable dozens of teams to move faster—from raw data to production-ready insights. The focus is on building systems that are reliable, repeatable, and easy for other teams to adopt at scale.

As a Senior Data Engineer (L7), you will design and build core platform capabilities such as data pipelines, onboarding patterns, and shared services that support analytics and AI workloads. You will work closely with platform teams, AI Engineers, and product teams to ensure that data systems are robust, scalable, and aligned to enterprise standards.

This role is ideal for an engineer who combines strong data engineering fundamentals with a platform mindset, and who takes pride in building systems that other teams depend on.
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Role & Responsibilities

Data Platform Engineering

• Design, build, and maintain scalable data pipelines and platform services that support multiple product teams.
• Develop reusable patterns for data ingestion, transformation, and serving, prioritizing reliability, consistency, and ease of adoption.
• Build and improve services for customer data onboarding, ensuring strong controls around security, isolation, and governance.
• Contribute to the development of data and AI platform capabilities that support analytics, machine learning, and emerging intelligent applications.

• Translate business and product requirements into well-designed data architectures and pipeline solutions.
• Implement batch and streaming data workflows using modern cloud data technologies (e.g., Spark, Databricks, Airflow, cloud-native storage).
• Apply best practices for data modeling, schema management, and pipeline performance optimization.
• Ensure systems are designed with scalability, maintainability, and cost efficiency in mind.

• Contribute to platform automation efforts that simplify how teams build and deploy data pipelines.
• Build tooling, templates, or services that reduce manual effort and enable consistent engineering practices.
• Support adoption of standardized deployment, provisioning, and operational workflows across teams.

• Ensure data systems meet requirements for reliability, observability, data quality, and performance.
• Monitor and troubleshoot production pipelines, performing root cause analysis and implementing improvements.
• Contribute to CI/CD practices, testing strategies, and operational runbooks for data systems.

• Partner with Software Engineers, AI Engineers, and Data Scientists to deliver integrated, end-to-end solutions.
• Collaborate with platform, infrastructure, and governance teams to align on standards and shared capabilities.
• Contribute to technical discussions, design reviews, and architecture decisions within the team.

• Bachelor’s degree in Computer Science, Engineering, Data Engineering, or equivalent practical experience.
• Strong experience building and operating data pipelines and distributed data systems in production environments.
• Hands-on experience with modern cloud data platforms (e.g., Databricks, Spark, Airflow, or equivalent).
• Solid understanding of data engineering fundamentals, including ETL/ELT patterns, data modeling, schema evolution, and data quality practices.
• Strong software engineering fundamentals, including system design, testing, and version control.
• Experience working with CI/CD and production operations, including monitoring and incident response.
• Proven ability to independently deliver well-scoped systems or components with high quality and reliability.

• Experience supporting machine learning or AI workloads (e.g., feature pipelines, data for model training or inference).
• Familiarity with platform engineering principles (reusability, standardization, developer tooling).
• Experience working in governed or regulated environments with strong data security requirements.

• Work independently on complex components or systems
• Contribute to system design and influence technical direction
• Deliver high-quality, production-ready solutions
• Partner effectively across teams while continuing to grow toward broader technical leadership

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.