Data Engineer II

About the job

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

Job Title

Data Engineer II

Overview

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 and networks, partnerships, and passion, our innovations help individuals, financial institutions, governments, and businesses realize their greatest potential.

The Mastercard Services organization is a key differentiator, delivering cutting-edge solutions used by some of the world’s largest organizations to make critical business decisions. Focused on innovation and scale, Services provides data-driven capabilities across consulting, analytics, experimentation, and risk management.

Team Overview

As part of Mastercard’s Data Platform & Orchestration team, you will contribute to building next-generation data platforms that are critical to our global data ecosystem.

Our team develops and operates scalable platform capabilities, including:

Cloud-native infrastructure and application provisioning

Standardized CI/CD pipelines and engineering tooling

Reusable frameworks and data platform components

These platforms enable teams to build, deploy, and operate data-driven solutions efficiently and securely at scale.

Role Overview

Data Platform & Orchestration is seeking a Data Engineer I to contribute to the development of cloud-native data platforms supporting Mastercard's global data ecosystem.

This role is ideal for an early-career engineer who is passionate about data engineering, distributed systems, and cloud technologies. You will work closely with senior engineers to build, test, deploy, and support scalable data solutions that power critical business capabilities.

You will gain hands-on experience with modern data engineering technologies including Spark, Kafka, cloud platforms, and data processing frameworks while contributing to high-impact projects across Mastercard's data landscape.

Key Responsibilities

Develop and maintain batch and near real-time data pipelines using Java, Python, Spark, and SQL

Build and support ETL/ELT pipelines for processing structured and semi-structured data

Contribute to the development of scalable data processing solutions across Data Lake and Data Warehouse environments

Assist in developing real-time data ingestion and streaming solutions using Kafka and Spark Structured Streaming

Perform data validation, reconciliation, and quality checks to ensure reliable data delivery

Collaborate with senior engineers to troubleshoot and resolve data pipeline and production issues

Write efficient SQL queries and optimize data processing jobs for performance and scalability

Develop and deploy applications and data pipelines in cloud environments such as AWS, Azure, or GCP

Contribute to automation, monitoring, and observability initiatives to improve platform reliability

Support CI/CD activities including code integration, testing, deployment, and release processes

Participate in code reviews and follow engineering best practices for secure and maintainable software development

Build reusable components and utilities that improve team productivity and consistency

Collaborate effectively with product owners, architects, data engineers, and platform teams

Support AI and machine learning initiatives by developing, validating, and preparing data pipelines used for analytics, predictive modeling, and Generative AI applications

Explore modern AI-enabled data engineering capabilities, including metadata-driven pipelines, data quality automation, and intelligent operational monitoring

Continuously learn and adopt new technologies, tools, and engineering practice

Required Skills & Qualifications

1-2 years of experience in software engineering, data engineering, or related technical roles

Knowledge of Java (JDK 8+) or Python programming, Good to have AI exposure

Understanding of object-oriented programming concepts and software development fundamentals

Familiarity with REST APIs and microservices concepts

Basic hands-on experience with Apache Spark, SQL, and data processing concepts

Understanding of ETL/ELT workflows and data pipeline architectures

Knowledge of relational databases and data modeling fundamentals

Basic understanding of Kafka or other messaging platforms

Familiarity with distributed systems concepts and data processing at scale

Experience or academic exposure to AWS, Azure, or GCP

Familiarity with cloud storage and compute services such as S3, ADLS, Databricks, or similar platforms

Basic understanding of containerization technologies such as Docker

Familiarity using Git for source code management, CI/CD tools such as Jenkins, GitHub Actions, or similar platforms

Understanding of software testing concepts and unit testing frameworks

Exposure to monitoring and logging tools is a plus

Basic understanding of AI/ML concepts and how data engineering supports model development and deployment

Familiarity with Python-based data analysis libraries such as Pandas or NumPy is a plus

Interest in Generative AI, Large Language Models (LLMs), or AI-powered data solutions is desirable

Strong analytical and problem-solving skills

Good verbal and written communication skills

Ability to learn quickly and adapt to new technologies

Ability to work effectively in a fast-paced global environment

Education

Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field

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.