Data Engineer II
Mastercard · Posted Oct 28
Global technology company connecting consumers, financial institutions, merchants, and businesses through secure payment processing and digital commerce solutions
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About the role
Mastercard's Data Platform & Orchestration team builds and operates scalable, cloud-native data platform capabilities — including infrastructure and application provisioning, standardized CI/CD pipelines and tooling, and reusable data platform frameworks — that support Mastercard's global data ecosystem. The role sits within Mastercard Services, which delivers data-driven capabilities across consulting, analytics, experimentation, and risk management. As a Data Engineer II, you will work with senior engineers to build, test, deploy, and support batch and near real-time data pipelines using Java, Python, Spark, Kafka, and SQL across cloud environments such as AWS, Azure, or GCP.
What you will do
- 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
Skills used in this role
What the employer is looking for
- 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
- Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field
Benefits and support
- Compensation and benefits are detailed in the job posting
About Mastercard
Mastercard is a global technology company in the payments industry that connects consumers, financial institutions, merchants, governments, and businesses worldwide. It operates a fast and secure payment processing network that spans more than 200 countries and territories. Through innovative products and solutions in credit, debit, digital assets, and security, Mastercard makes commerce safer, simpler, and more accessible.
- Industry
- Payments
- Company size
- 10001+ employees
- Founded
- 1966
- Location
- Purchase, New York, USA
- Funding stage
- Public Company
Funding
Public Company · $115M raised
Leadership
Chief Executive Officer
Chief Business Officer
President & Chief Technology Officer
Chief People Officer
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