Director of Data Engineering

About the role

Mastercard is seeking a Director of Data Engineering to shape the strategy, architecture, and delivery of the data platform that powers analytics and agentic AI applications across multiple business verticals. This senior, hands‑on technical leadership role will ensure data is reliable, governed, and ready for AI consumption at production scale.

Key responsibilities

• Define and execute the data engineering strategy for the CNPF Data & AI organisation, with a focus on AI and GenAI products.
• Architect and deliver data foundations for multi‑agent systems, including MCP servers, retrieval pipelines, vector stores, feature stores, and knowledge graphs.
• Design context‑engineering infrastructure that enables agents to reason over Mastercard data safely, with proper grounding, freshness, and access controls.
• Lead lakehouse, streaming, and event‑driven platform design using Databricks, Spark, Kafka, Delta Lake or Iceberg to support batch analytics and low‑latency AI use cases.
• Ensure data systems meet Mastercard standards for governance, lineage, quality, observability, and risk, incorporating AI‑specific requirements such as PII handling and audit trails.
• Set technical standards for exposing data products to agents and applications.

Required profile

• Senior technical leader with extensive experience in data engineering and large‑scale data platforms.
• Proven ability to collaborate with Applied AI, Product, and Architecture teams.
• Strong understanding of AI/LLM consumption patterns and associated compliance needs.

Required skills

• Databricks
• Apache Spark
• Apache Kafka
• Delta Lake
• Iceberg
• Vector stores
• Feature stores
• Knowledge graphs
• Data governance
• Data lineage
• Data quality
• Observability
• PII handling
• Prompt/response logging
• Audit trails
• MCP servers
• Retrieval pipelines
• AI
• LLM