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Sobre este puesto de Software engineer II (Java, Apache/ Spark, AWS and ETL) en Mastercard

Mastercard · Presencial · Pune, India

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

Software engineer II (Java, Apache/ Spark, AWS and ETL)

Software Engineer II (ETL, AWS, Spark, Java)
Overview
We are seeking a Software Engineer II to design, develop, and maintain scalable data processing and cloud-native solutions. The ideal candidate will have experience in Java, Apache Spark, AWS, and ETL engineering, with a strong focus on building reliable, high-performance data platforms.
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Role & Responsibilities
• Design and develop ETL pipelines and large-scale data processing solutions using Apache Spark.
• Build and support backend services, APIs, and data platforms using Java and Spring Boot.
• Develop and deploy cloud-native applications on AWS.
• Ensure data quality, performance, security, and operational excellence across applications.
• Contribute to CI/CD, monitoring, automation, and production support activities.
• Collaborate with cross-functional teams and participate in Agile development practices.

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Required Qualifications
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 4+ years of software engineering experience.
• Strong experience with Java, Spring Boot, Apache Spark, ETL development, and SQL.
• Experience with AWS services and cloud-native application development.
• Hands-on experience with relational databases, Git, and software engineering best practices.
• Familiarity with Docker, Kubernetes, CI/CD pipelines, and Agile methodologies.

________________________________________
Preferred Qualifications
• Experience with Databricks, Kafka, Snowflake, Redshift, or similar data technologies.
• Knowledge of microservices, distributed systems, and Infrastructure as Code (Terraform).
• Experience with observability and monitoring tools such as Splunk, Dynatrace, or CloudWatch.
• Financial services or payments industry experience.

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Key Competencies
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities.
• Ownership mindset with a focus on quality, reliability, and continuous improvement.
• Ability to work independently while contributing to team success.

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Success Measures
The successful candidate will:
• Deliver scalable and reliable data processing solutions.
• Improve performance and efficiency of ETL workloads.
• Ensure high-quality software with strong operational excellence.
• Drive cloud adoption and engineering best practices.
• Mentor team members and contribute to technical leadership initiatives.
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Typical Technology Stack
Area Technologies
Programming Java, Spring Boot
Big Data Apache Spark, Spark SQL
Cloud AWS S3, EMR, Glue, Lambda, ECS/EKS
Messaging Kafka, Axon
Databases Oracle, PostgreSQL, MySQL
DevOps Jenkins, GitHub Actions, Terraform
Monitoring Splunk, Dynatrace, CloudWatch
Containers Docker, Kubernetes

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.




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Sobre Mastercard

Everyone wants easier ways to pay; we invent them. Checkout lines are slow; we speed them along. Merchants want more sales; we give them data and insights. People need financial access; we connect them. Corporate purchasing is complicated; we make it simple. Commuters are busy; we speed them on their way. Governments need greater efficiencies; we help create them. Small businesses are virtual; we give them access to a world of buyers. Retailers want to fight fraud; we provide the tools.

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