Data Engineer II

Posted Yesterday
Be an Early Applicant
Pune, Mahārāshtra, IND
Hybrid
Mid level
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
We are a global technology company in the payments industry.
The Role
Design, build, and operate scalable batch and near-real-time data pipelines and microservices using Java, Spark, and cloud-native technologies. Enable ETL/ELT across Data Lakes and Warehouses, ensure data quality and performance, deploy on cloud (AWS/Azure/GCP), leverage CI/CD and IaC, implement monitoring and observability, troubleshoot production systems, and mentor junior engineers.
Summary Generated by Built In
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
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 II to design and build next-generation, cloud-native data platforms supporting Mastercard's global data ecosystem.
In this role, you will lead the development of scalable batch and real-time data pipelines, enabling efficient data processing across Data Lakes and Data Warehouses. You will work at the intersection of data engineering, cloud platforms, and distributed systems, contributing to high-impact initiatives and driving engineering excellence.
This role is ideal for someone who thrives in a fast-paced, collaborative environment, enjoys solving complex data challenges, and is passionate about building resilient, high-performance systems at scale.
Role Overview
As a Data Engineer II, you will design and develop scalable batch and near real-time data pipelines that power Mastercard's analytics and operational systems.
You will work across data engineering, cloud platforms, and distributed systems, building robust data solutions on top of Data Lakes and Data Warehouses. This role is highly hands-on and requires strong engineering fundamentals, with opportunities to influence design decisions and mentor junior engineers.
You will contribute to building cloud-native data platforms, enabling reliable, high-performance data processing at scale.Key Responsibilities• Design and build scalable data pipelines and microservices using Java (Spring Boot), Spark, and cloud-native technologies• Develop high-throughput, low-latency data processing systems for real-time and batch workloads• Design and develop batch and near real-time data pipelines using Spark, Kafka, and Java-based frameworks• Build and maintain ETL/ELT pipelines for structured and unstructured data• Develop data processing solutions across Data Lakes and Data Warehouse environments• Contribute to stream processing use cases (Kafka, and optionally Flink or Spark Structured Streaming)• Ensure data quality, validation, and reliability across pipelines• Optimize data processing workloads for performance and scalability• Develop and deploy data pipelines on AWS, Azure, or GCP• Leverage cloud-native services such as S3/ADLS/GCS, EMR/Databricks, BigQuery/Redshift/Snowflake• Contribute to Infrastructure as Code (Terraform, CloudFormation, or equivalent)• Build solutions with high availability, fault tolerance, and scalability• Follow best practices for secure data processing and cloud resource utilization• Follow best practices in coding, testing, and CI/CD pipelines• Contribute to automation, monitoring, and observability of data pipelines• Develop reusable components to improve engineering efficiency and consistency• Participate in code reviews and design discussions• Collaborate with architects, product teams, and cross-functional stakeholders• Support production deployments and troubleshoot issues in distributed systems• Contribute to a culture of continuous improvement and technical excellence• Mentor junior engineers and share knowledge within the team
Required Skills & Qualifications• Strong proficiency in Java (JDK 8+), OOP/OOAD principles, Python is a plus. Experience with Spring Boot, REST APIs, Spring Security, Hibernate• Hands-on experience with distributed systems, multithreading, and messaging systems (Kafka preferred)• Hands-on experience with Apache Spark (Core, SQL, or Structured Streaming). Experience with Kafka or similar messaging/streaming platforms• Understanding of ETL/ELT pipelines, batch and streaming architectures• Familiarity with data formats (Parquet, Avro, ORC)• Basic understanding of data modeling (star/snowflake schemas). Understanding of distributed systems and multithreading concepts• Hands-on experience with at least one cloud platform: AWS, Azure, or GCP• Experience using cloud storage and compute services (e.g., S3, ADLS, Databricks, EMR)• Familiarity with containerization (Docker) and basic Kubernetes concepts• Exposure to Infrastructure as Code tools is a plus• Strong SQL skills and experience working with relational and analytical databases• Exposure to Data Lakes and Data Warehousing platforms• Familiarity with workflow orchestration tools (Airflow or similar)• Experience with CI/CD tools (Jenkins, GitHub Actions, or similar)• Good understanding of unit testing (JUnit or equivalent)• Familiarity with monitoring tools (Splunk, Prometheus, Grafana, etc.)• Awareness of secure development practices• Experience with real-time processing frameworks -Spark Streaming, good to have knowledge on Apache Flink • Exposure to performance testing tools (JMeter, Gatling)• Familiarity with DevSecOps or SRE concepts• Experience improving automation and developer productivity• Strong problem-solving and analytical skills. Ownership mindset with ability to deliver independently• Good communication and collaboration skills. Passion for learning new technologies and improving engineering practices• 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.

Skills Required

  • Strong proficiency in Java (JDK 8+) and OOP/OOAD principles
  • Experience with Spring Boot, REST APIs, Spring Security, Hibernate
  • Hands-on experience with distributed systems and multithreading
  • Experience with Apache Spark (Core, SQL, or Structured Streaming)
  • Experience building batch and streaming ETL/ELT pipelines and architectures
  • Hands-on experience with messaging/streaming platforms (Kafka)
  • Familiarity with data formats Parquet, Avro, ORC
  • Basic understanding of data modeling (star/snowflake schemas)
  • Hands-on experience with at least one cloud platform: AWS, Azure, or GCP
  • Experience using cloud storage and compute services (S3, ADLS, GCS, EMR, Databricks, BigQuery, Redshift, Snowflake)
  • Strong SQL skills and experience with relational and analytical databases
  • Familiarity with containerization (Docker) and basic Kubernetes concepts
  • Familiarity with workflow orchestration tools (Airflow or similar)
  • Experience with CI/CD tools (Jenkins, GitHub Actions, or similar)
  • Good understanding of unit testing (JUnit or equivalent)
  • Familiarity with monitoring and observability tools (Splunk, Prometheus, Grafana)
  • Awareness of secure development practices and DevSecOps/SRE concepts
  • Experience improving automation and developer productivity
  • Bachelor's degree in Computer Science, Information Technology, Engineering, or related field
  • Python
  • Knowledge of Apache Flink
  • Exposure to Infrastructure-as-Code tools (Terraform, CloudFormation)
  • Exposure to performance testing tools (JMeter, Gatling)

What the Team is Saying

Jenny
Mastercard

Mastercard Compensation & Benefits Highlights

  • Retirement Support Company information highlights a 10% retirement match on U.S. roles, positioned as best‑in‑class and well above typical large‑employer benchmarks. This level of employer contribution materially strengthens long‑term savings.
  • Leave & Time Off Breadth U.S. postings list 25 vacation days, 5 personal days, 10 company holidays, 80 hours of paid sick/safe time, and up to 20 days of bereavement. A minimum of 16 weeks paid new‑parent leave (including adoption and foster) further expands paid time away.
  • Parental & Family Support Benefits include a minimum of 16 weeks paid new‑parent leave and family‑building support such as fertility, adoption, and surrogacy where legally available. Dependent scholarships, counseling, and protection benefits contribute additional family support.

Mastercard Insights

Am I A Good Fit?
beta
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.

The Company
HQ: Purchase, NY
38,800 Employees
Year Founded: 1966

What We Do

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re building a resilient 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.

Why Work With Us

We live the Mastercard Way: creating value in the communities we touch, growing together through the opportunities we see, and moving fast to innovate and scale. Our collaborative culture and our passionate people are the key to what we do, driving meaningful change as one team and connecting everyone to priceless possibilities.

Gallery

Gallery
Gallery
Gallery
Gallery
Gallery
Gallery
Gallery
Gallery
Gallery

Mastercard Teams

Team
Technology
Team
Cybersecurity and Threat Intelligence
Team
AI and Data
About our Teams

Mastercard Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

In our ongoing workplace evolution, we’ve introduced hybrid work, Work-From-Elsewhere Weeks and Meeting-Free Days.

Typical time on-site: 3 days a week
Company Office Image
HQPurchase, NY
Arlington, VA
Company Office Image
Atlanta, GA
Bogotá, CO
Boston, MA
Chicago, IL
Company Office Image
Dublin, Dublin
Gurugram, Gurugram
Company Office Image
London, GB
Company Office Image
Miami, FL
Mumbai, Maharashtra
Company Office Image
New York, NY
Company Office Image
O'Fallon, MO
Company Office Image
Pune, Maharashtra
Ramat Gan, IL
Company Office Image
Saint Leonards, St Leonards
San Francisco, CA
São Paulo, SP
Seattle, WA
Singapore, SG
Company Office Image
Toronto, Ontario
Vancouver, BC
Learn more

Similar Jobs

Mastercard Logo Mastercard

Data Engineer

Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
Hybrid
Pune, Mahārāshtra, IND
38800 Employees

Mastercard Logo Mastercard

Manager, Software Engineering

Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
Hybrid
Pune, Mahārāshtra, IND
38800 Employees

Mastercard Logo Mastercard

Lead, Platform Engineering

Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
Hybrid
Pune, Mahārāshtra, IND
38800 Employees

Mastercard Logo Mastercard

Software Engineer

Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
Hybrid
Pune, Mahārāshtra, IND
38800 Employees

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account