Director, Data engineering

Mastercard
Dublin
Workplace: OnsiteFull timeFunction: Executive & General ManagementSkills: ["Technical communication","Leadership","Architectural thinking","Player-coach","Cross-functional alignment"]

Lead the strategy, architecture, and delivery of the data platform powering analytics products and agentic AI applications. Own the data backbone for LLM agents and MCP servers—ensuring reliability, governance, real-time retrievability, and production readiness. Design multi-agent data foundations (retrieval pipelines, vector/feature stores, knowledge graphs), build context-engineering infrastructure, and drive secure lakehouse/streaming/event-driven platform design on Databricks, Spark, Kafka, and Delta/Iceberg.

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FursaFursa
Mastercard
Mastercard
3 months ago

Director, Data engineering

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Status: Live
Reposted: similar role first listed 5 months ago

Job Summary

Lead the strategy, architecture, and delivery of the data platform powering analytics products and agentic AI applications. Own the data backbone for LLM agents and MCP servers—ensuring reliability, governance, real-time retrievability, and production readiness. Design multi-agent data foundations (retrieval pipelines, vector/feature stores, knowledge graphs), build context-engineering infrastructure, and drive secure lakehouse/streaming/event-driven platform design on Databricks, Spark, Kafka, and Delta/Iceberg.
Location: Dublin
Workplace: Onsite
Employment Type: Full time
Job Function: Executive & General Management
Seniority: Director level

Key Responsibilities

  • •Own the data engineering strategy and technical direction for CNPF, focusing on agentic AI and GenAI products in production.
  • •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 for safe agent reasoning over Mastercard data, including grounding, freshness, and access controls.
  • •Drive lakehouse, streaming, and event-driven platform design to support batch analytics and low-latency AI use cases.
  • •Guide a team of senior data engineers through technical direction and growing their capability over time.

Key Requirements

  • •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).
  • •Strong hands-on background in data architecture, modeling, streaming, and lakehouse design on AWS.
  • •Proven track record taking data systems from concept to secure, scalable production.
  • •Solid grasp of data governance, lineage, quality, and observability frameworks.
Skills:Technical communicationLeadershipArchitectural thinkingPlayer-coachCross-functional alignment
Tech Stack:DatabricksSparkKafkaDelta/IcebergDbtAWSMCP (Model Context Protocol)Vector storesFeature storesKnowledge graphsLakehouseStreamingEvent-driven systemsLLMOpsRetrieval pipelines

Company Brief

Mastercard
Mastercard is a global payments and technology company that processes transactions, provides fraud prevention and data services, and builds payment infrastructure for consumers, businesses, merchants and governments across 200+ countries.
Industry: Payments
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Purchase, New York, United States
Founded: 1966
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