Lead, Data Engineer

Mastercard is hiring a Lead, Data Engineer in Pune.

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 Lead, Data Engineer

Responsibilities

• Act as a subject matter expert in data engineering, providing technical leadership and influencing stakeholders to support team priorities, solution development, and continuous improvement.
• Conduct thorough code reviews and provide constructive feedback to promote engineering standards, maintainability, and overall solution quality.
• Design, develop, and maintain scalable data pipelines and solutions that meet expectations for performance, data quality, security, observability, and operational resilience.
• Develop and maintain technical documentation such as requirements, solution designs, test strategies, and deployment, migration, and rollback plans to support reliable delivery.
• Document technical solutions, processes, standards, and methodologies to support knowledge sharing, reproducibility, governance, and continuous improvement.
• Stay current with data engineering tools, frameworks, and industry best practices, and help drive adoption of improvements that enhance platform capabilities and operational efficiency.
• Contribute to solution and technology roadmaps by supporting strategic planning, modernization efforts, and innovation while reinforcing best practices in data quality, testing, and security.
• Perform some ML Engineering related tasks such as operationalizing models and deploying them
• Mentor and support junior team members through coaching, work reviews, and knowledge sharing, helping build technical capability and a culture of continuous improvement.

Requirements

• Significant experience in data engineering, including the design and operation of scalable data pipelines, platforms, and integrations across structured, semi-structured, and unstructured data.
• Demonstrated ability to lead technical design efforts, conduct code reviews, and establish engineering standards that improve reliability, maintainability, and scalability.
• Strong hands-on experience with modern data engineering and orchestration tools, cloud or enterprise data platforms, and practices related to monitoring, observability, and secure data processing. Ideal candidate has experience with building pipelines and onboarding data to Cloudera.
• Strong written and verbal communication skills, with the ability to influence stakeholders, translate technical concepts for diverse audiences, and produce clear technical documentation.
• Experience mentoring engineers and collaborating across technical, operational, and business teams to support roadmap execution, governance, and continuous improvement.

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.

About Mastercard

The Lead Data Engineer, AI Ops serves as a technical leader responsible for designing, building, and evolving scalable data solutions that support operational visibility, analytics, and intelligent decision-making across AI Ops, SRE, infrastructure, and software engineering teams. This role provides technical direction, partners closely with stakeholders, and applies deep expertise to improve products, processes, and engineering practices. The position also helps establish standards for data qua