Director, Data engineering

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

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 realise 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

The CNPF Data & AI organisation is looking for a Director of Data Engineering to lead the strategy, architecture, and delivery of the data platform powering our analytics products and agentic AI applications across Small & Medium Enterprise (SME), Corporate Solution, Transfer Solution and Commercial Verticals.

This is a senior, hands-on technical leadership role within Data & AI Product Enablement. The Director will own the data backbone that our LLM agents, MCP servers, and analytics products run on - making sure data is reliable, governed, retrievable in real time, and ready for AI consumption at production scale. The role works in close partnership with Applied AI, Product, and Architecture leadership.

Role

Own the data engineering strategy and technical direction for CNPF, with a strong focus on enabling agentic AI and GenAI products in production

Architect and deliver the data foundations for multi-agent systems - including MCP servers exposing data and tools to agents, retrieval pipelines, vector stores, feature stores, and knowledge graphs

Lead the design of context-engineering infrastructure that lets agents reason over Mastercard data safely, with the right grounding, freshness, and access controls

Drive lakehouse, streaming, and event-driven platform design (Databricks, Spark, Kafka, Delta/Iceberg) to support both batch analytics and low-latency AI use cases

Ensure data systems meet Mastercard standards for governance, lineage, data quality, observability, and risk - including the additional requirements that come with AI consumption (PII handling, prompt/response logging, audit trails)

Set technical standards for how data products are exposed to agents and applications, including MCP design patterns, schema contracts, and tool interfaces

Partner with Applied AI on evaluation and runtime data needs - training sets, eval datasets, retrieval quality, and feedback loops

Stay hands-on enough to make sharp architectural calls, review designs, and unblock the team on hard problems

Guide a team of senior data engineers, providing technical direction and growing their capability over time

ALL ABOUT YOU

Significant experience leading the design and delivery of large-scale data platforms in production

Deep expertise in distributed data processing and the modern data stack - Spark, Databricks, Kafka, dbt, Delta/Iceberg, and similar

Strong hands-on background in data architecture, modelling, streaming, and lakehouse design on AWS

Proven track record of taking data systems from concept to secure, scalable production

Solid grasp of data governance, lineage, quality, and observability frameworks

Excellent technical communication - able to align engineers, AI scientists, product managers, and executives

Comfortable operating as a player-coach: setting direction, reviewing designs, and going deep when needed

What Makes You Stand Out

You have personally built data infrastructure that powers agentic AI in production - not just analytics dashboards

Hands-on experience designing and operating MCP (Model Context Protocol) servers, including authentication, tool exposure, schema design, and observability

Direct experience building the data layer for multi-agent systems - retrieval, memory, state management, long-running workflow data, and human-in-the-loop checkpoints

Strong familiarity with vector databases, hybrid retrieval (semantic + structured), and knowledge graph integration with LLMs

Practical understanding of LLMOps data needs - eval datasets, golden traces, prompt/response telemetry, and feedback capture

Experience designing real-time and event-driven systems that support low-latency agent decisioning

Sharp instincts for the trade-offs between batch and streaming, structured and unstructured, accuracy and cost - and how those decisions cascade into agent behaviour

Experience partnering with security and governance teams to ship AI-facing data products responsibly at enterprise scale

Corporate Security Responsibility

Every person working for, or on behalf of, Mastercard is responsible for information security. All activities involving access to Mastercard assets, information, and networks come with inherent risk and therefore it is expected that the successful candidate will:

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

Complete all mandatory security trainings in accordance with Mastercard's guidelines

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.