Lead Data Engineer

About the role

Mastercard is seeking a Lead Data Engineer to join our team in . 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.

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.

Lead Data Engineer

Who is Mastercard?

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.

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.