Senior Solutions Architect (Data & Risk)

About the role

Our client, a major financial services firm, is looking for a Senior Solutions Architect to design and deliver data‑focused solutions in a critical business area. This is a hybrid, daily‑rate contract position based in South Dublin.

Key responsibilities

• Design and document end‑to‑end solutions that address complex business and technical challenges.
• Establish and promote architecture principles, coding standards, and CI/CD best practices across teams.
• Lead proof‑of‑concept and research initiatives to explore emerging technologies.
• Collaborate with risk, compliance, and engineering stakeholders to shape technical solutions aligned with business objectives.
• Produce high‑quality architecture artefacts such as UML models, process flows, and technical documentation for executives, auditors and engineering teams.
• Provide guidance on technology choices, vendor assessments and cost/benefit trade‑offs for enterprise risk platforms.
• Mentor engineering teams and encourage adoption of secure, resilient, risk‑aware design patterns.

Required profile

• Extensive experience as a Solutions Architect, preferably in financial services or a similarly regulated industry.
• Strong background in building distributed, micro‑service or service‑oriented systems deployed on container platforms (Kubernetes, Docker).
• Hands‑on expertise with data‑intensive systems, including ETL workflows, batch and stream processing, and high‑volume data pipelines.
• Ability to design solutions that combine relational (PostgreSQL, SQL Server) and NoSQL (MongoDB) databases.
• Experience developing and integrating APIs (REST, GraphQL) and event‑driven architectures (Kafka, Redis Streams, message queues).

Required skills

• Microservices / Service‑oriented architecture
• Kubernetes, Docker
• ETL, batch processing, stream processing
• PostgreSQL, SQL Server, MongoDB
• REST, GraphQL APIs
• Kafka, Redis Streams, message queues
• UML, Visio diagramming
• Python (for prototyping and PoC)
• Time‑series databases (Prometheus, InfluxDB, TimescaleDB) – nice to have
• Graph databases (Neo4j, TigerGraph) – nice to have