Lead Data Engineer

Mastercard Inc.; Hyderabad; On-site; INR 3,500,000 - 5,000,000; Full time

Job summary

Mastercard Inc. in Hyderabad, India, is seeking a Lead Data Engineer to steer design standards and architecture for scalable data platforms. This senior IC role balances hands-on engineering with technical leadership to raise engineering quality across teams.

You will set governance for Databricks, Spark, Python, PySpark, and dbt, while mentoring engineers and aligning with product roadmaps in a fast-growing fintech landscape.

Qualifications

• 8+ years of data engineering experience with leadership.
• Expert hands-on with Databricks, Spark, Python, and PySpark.
• Deep dbt and CI/CD expertise (GitLab, Jenkins).
• Ability to define engineering standards and drive team practices.
• Strong architecture and platform ownership across observability and performance.
• Excellent communication with stakeholders; banking/fintech exposure a plus.

Responsibilities

• Set design standards and best practices for pipelines built on Databricks and Spark.
• Provide technical leadership, reviews, and architecture oversight.
• Lead CI/CD, DataOps, and data observability strategy.
• Oversee Databricks administration and deployment governance.
• Mentor engineers and foster a strong code review culture.
• Collaborate with product and stakeholders on roadmaps and trade-offs.
• Own deployment, migration, and upgrade strategies for data platforms.

Skills

Databricks

Spark

Python

PySpark

dbt

CI/CD

GitLab

Jenkins

Technical leadership

Data platform architecture

Education

Bachelor's or Master's degree in Computer Science or related technical field

Tools

Databricks

dbt

GitLab

Jenkins

Job description

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

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 and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.

Overview

Mastercard is seeking a Lead Data Engineer to join our team in Hyderabad, India. This is a senior individual-contributor and technical leadership role that drives design standards and guides a team's engineering practices. It will appeal to you if you combine deep technical mastery with the ability to lead the technical direction of a team and elevate its overall engineering quality. You will set the technical bar for how we build and operate data platforms at scale, balancing hands‑on architecture with team leadership. Our teams are small, agile, and focused on the needs of the high growth fintech marketplace, and you will work across functional teams within Mastercard to deliver on our cloud strategy.

Key Responsibilities

Set and enforce design standards, patterns, and best practices for pipelines built on Databricks, Spark, Python, PySpark, and dbt. Provide technical leadership and direction to a team of engineers, owning architecture and design reviews. Lead the design of CI/CD (GitLab, Jenkins), DataOps, and data observability strategy for the team. Own Databricks platform administration standards and deployment governance using Databricks Asset Bundles. Drive resolution of complex technical challenges across pipelines and the platform. Mentor and grow engineers, establishing a strong code review and quality culture. Partner with product and stakeholders on roadmap, prioritization, and technical trade-offs. Own the deployment, migration, and upgrade strategy for the team's data platforms.

Required Qualifications

Bachelor's or Master's degree in computer science or a related technical field. 8+ years of data engineering experience, including demonstrated technical leadership. Expert hands‑on experience with Databricks (including administration), Spark, Python, and PySpark. Deep dbt/TDD and CI/CD (GitLab, Jenkins) expertise. Proven ability to define engineering standards and lead a team's practices. Strong architecture and platform ownership across observability, cost, and performance. Excellent communication and stakeholder management skills. Ideally you have experience in banking, e-commerce, credit cards or payment processing and exposure to both SaaS and premises‑based architectures. In addition, you have a post‑secondary degree in computer science, mathematics, or quantitative science.

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.

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.