Mastercard
Budapest, Hungary
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.
Principal Engineer – Data Platform (Identity Solutions)
Principal Engineer – Data Platform (Identity Solutions)
We are looking for a Principal Engineer to join the Identity Solutions Data Platform team, the platform underlying Mastercard's Identity Graph and Identity Network, which continuously processes terabytes of data and tens of billions of records to help detect and prevent fraud for customers worldwide.
Role
You will assess our data processing pipelines against cost, efficiency, and reliability targets, prototyping solutions to validate feasibility and measuring results against clear KPIs. You will then work with engineers, product managers, and business stakeholders to build the case for change. You will provide hands-on technical leadership: setting the standard for engineering quality through your own work, developing lead and senior engineers, and identifying gaps in our development practices with the same methodical, evidence-based approach. You will also maintain a clear view of how our platform fits into the broader Mastercard technology ecosystem, anticipating the needs of partner teams and identifying opportunities to consolidate on shared platforms.
All About You
A track record of delivering complex systems through personal depth and attention to detail, with the ability to design an architecture, write and review code, and hold high standards for quality at every level of the stack.
Deep experience designing and operating large-scale data processing pipelines, with the ability to reason about tradeoffs in pipeline architecture, cost, performance, and reliability.
Experienced with distributed systems, cloud infrastructure (AWS), security, and reliability engineering.
Extensive hands-on experience with Spark and Databricks; proficiency in Scala or Java, with Python experience a plus.
Able to assess technical proposals with data: prototyping to validate feasibility and defining measurable success criteria to support clear recommendations.
Familiar with machine learning workflows, including feature engineering, model training, and the data infrastructure requirements that support them.
Able to review requirements critically and collaboratively, asking whether something is truly needed, proposing alternatives, and surfacing concerns early, while keeping the team moving forward.
Clear communicator who can explain technical decisions to engineers, product owners, and business stakeholders at the right level of detail.
Committed to mentoring the engineers you work with, patient in explaining complex topics and generous with your time and knowledge.
Aware of how the team's work fits into the broader organization, proactive in communicating across teams, and alert to opportunities to share platforms and avoid duplicated effort.
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: