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Mastercard

Processes payments across a global network

Senior Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timePune, Maharashtra, IndiaNo salary listedIn-person

About the Job

Requirements

  • Demonstrated ability to learn independently and acquire new skills and knowledge.
  • Strong independent research skills and resourcefulness in finding solutions and innovating in data engineering.
  • Strong understanding of data pipelines and end-to-end machine-learning model development workflows, with exposure to entity-centric data systems.
  • Experience with Python and SQL, including writing clean, readable, and maintainable code.
  • Experience with big data technologies such as Spark and distributed computing frameworks.
  • Hands-on experience with cloud platforms such as Databricks, AWS, or GCP.
  • Experience collaborating across data science, engineering, and governance teams.
  • Familiarity with Agile methodologies and iterative delivery and cross-team collaboration.
  • Bachelor’s degree in Computer Science, Data Analytics, Mathematics, Software Engineering, or a related field, or equivalent practical experience.
  • Contributions to platform standardization, reusability, and shared tooling across teams.
  • Abide by Mastercard’s security policies and practices, protect the confidentiality and integrity of accessed information, report suspected security violations or breaches, and complete mandatory security training.

Responsibilities

  • Contribute to collaborative projects and share insights to advance engineering and data science excellence.
  • Work with big data platforms such as Databricks and Apache Spark at petabyte scale for data processing and model enablement.
  • Partner with Data Science teams to scale models, features, and experimentation into reliable systems.
  • Support deployment of model features and artifacts, integrating them into production environments and downstream decisioning systems.
  • Write clean, testable, maintainable, robust, efficient, production-grade code.
  • Design, build, and maintain data pipelines integrating multiple data sources for a unified merchant registry and trust profile.
  • Collaborate with data operations and governance teams to move and manage data in compliance with security standards, policies, and regulatory requirements.
  • Contribute to scalable, entity-centric data models for merchant identity resolution and longitudinal profiling.
  • Automate and maintain data workflows in distributed environments to improve reliability and operational efficiency.
  • Analyze and optimize ETL/ELT processes for high-performance data access and model execution.
  • Implement testing frameworks and monitoring capabilities for reliable, observable, continuously improving production solutions.
  • Support incident response, debugging, and performance tuning of production AI/ML systems.

Desired Qualifications

  • Experience working in hybrid cloud and on-premises environments.
  • Familiarity with machine-learning lifecycle and CI/CD practices for data and machine-learning workflows.
  • Experience with data governance, lineage, and metadata management.
  • Exposure to batch, streaming, or real-time data pipelines and production machine-learning monitoring and observability.
  • Experience supporting high-scale production systems in merchant, fraud, or payment domains.
  • Understanding of security, compliance, and handling sensitive data.
  • Experience designing scalable databases and data models such as business registries.
  • Experience with database updates and maintenance.

About the Company

Mastercard

Processes payments across a global network

Mastercard operates a global payment network connecting financial institutions, merchants, businesses and consumers. It authorizes, clears and settles transactions between participating institutions, while banks issue Mastercard-branded cards and extend credit to their customers. Its services also include fraud detection, identity verification, payment tokenization, data analysis and consulting for organizations managing commerce and financial operations. The company earns network fees linked to payment volumes and processed transactions, along with fees for its services and solutions. Founded by a group of banks in 1966, Mastercard is headquartered in Purchase, within Harrison, New York.

Company size
10,001+
Company stage
IPO
Headquarters
Town of Harrison, New York
Founded
1966

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