Fraud & Payments Platform Techno-Functional Lead

Citigroup; Dublin; Hybrid; EUR 93,000 - 140,000; Full time

Benefits offered by this job

Hybrid work model

Benefits package

Job summary

Citi Dublin is seeking a high-impact Development Lead with techno-functional expertise to join Global Payments Technology, building Fraud Detection & Analytical Platform across Payments. Requirements include Java, Spring Boot, Restful microservices, MongoDB/Oracle, real-time messaging (Confluent Kafka, IBM MQ), and deep payments domain knowledge.

This senior leader will blend engineering excellence with payments expertise, guiding architecture, delivery, and integration with fraud risk scoring

Qualifications

• Bachelor's or master's degree in computer science, information systems, finance technology, or a related field.
• 10+ years of experience in Payments domain with at least 6+ years in a techno-functional lead or lead analyst capacity.

Responsibilities

• Techno-functional leadership & solution architecture for end-to-end payment flows.
• Lead architecture, design reviews, and walkthroughs with architects, product owners, and operations.
• Oversee integration of payment engines with fraud detection platforms and risk scoring systems.
• Ensure non-functional requirements (NFRs) like throughput, latency, and 24/7 availability are met.

Skills

Java

Spring Boot

Restful microservices

Payments domain

Leadership

Agile delivery

Education

Bachelor's or Master's in CS/IS/Finance Tech

Tools

Kafka (Confluent)

IBM MQ

MongoDB

Oracle

ISO 20022

Job description

Citi Dublin is seeking a high-impact Development Lead with techno-functional expertise to join Global Payments Technology, building Fraud Detection & Analytical Platform across Payments. Requirements include Java, Spring Boot, Restful microservices, MongoDB/Oracle, real-time messaging (Confluent Kafka, IBM MQ), and deep payments domain knowledge.

This senior leader will blend engineering excellence with payments expertise, guiding architecture, delivery, and integration with fraud risk scoring