MastercardLead Data Engineer
AI in this role
Lead Data Engineer to set design standards and guide engineering practices for data platforms at scale using Databricks and Spark.
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 EngineerWho 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.
How we rate this
Lead Data Engineer at Mastercard rates 0 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
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Skills and AI tools this role asks for
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- Tell me about a project where data engineering was part of your work. What did you do?
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- Tell me about a project where data observability was part of your work. What did you do?
- Tell me about a project where architecture was part of your work. What did you do?
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- List these exact terms on your resume: Data Engineering, Ci Cd, Dataops, Data Observability, and Architecture. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
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