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3 Level Treasury Systems Support with FIS Integrity Treasury Application Our Client is looking to recruit a Level 3 Treasury Systems Specialist will be responsible for the configuration, integrity, and controlled evolution of the Treasury Management System and its integrations, ensuring that all system changes are delivered safely, efficiently, and aligned to Treasury requirements. Technical Platform Management & Treasury System Integrity. Ensures integrity, resilience, and controlled operation of the Treasury platform, safeguarding payment execution, liquidity visibility, risk processing, and accounting accuracy.  Configure and maintain FIS Integrity TMS workflows, parameters, and reference data  Manage integration architecture across banks, trading platforms, ERP, and market data providers  Ensure system configuration aligns with Treasury processes, control standards, and SaaS constraints  Maintain technical documentation and configuration baseline to support audit and traceability Complex Issue Resolution & Treasury Risk Containment Contains and resolves high impact issues that threaten Treasury operational integrity, financial risk exposure, or regulatory compliance.  Diagnose and resolve high‑severity system and integration issues  Perform cross‑system root‑cause analysis covering data, configuration, and integration layers  Implement corrective and preventative actions to reduce recurrence of Treasury‑impacting incidents  Analyse incident trends to strengthen platform resilience and reduce operational risk Release & Regression Governance with Treasury Assurance Protects Treasury outcomes during change by ensuring releases are safe, controlled, and aligned to business risk.  Define regression testing scope based on Treasury risk and process criticality  Validate system changes prior to release against technical and control criteria  Approve production deployments and technical release readiness Ensure release execution meets governance, audit, and SaaS requirements Controls, Configuration & Audit Governance Ensures Treasury systems remain audit ready, controlled, and compliant with segregation of duties and access policies.  Maintain configuration standards and SoD controls  Monitor system access and privileged configuration changes  Support internal and external audits with traceable configuration and change evidence  Ensure ongoing compliance with Company control and governance framework Enhancements & Project Delivery Supporting Treasury Outcomes Delivers platform enhancements that improve Treasury efficiency, accuracy, and control without introducing operational risk.  Deliver system enhancements and configuration improvements  Support Treasury projects and platform upgrades  Translate approved functional requirements into robust system design aligned to SaaS constraints The role operates as the second line of defence for Treasury technology risk, safeguarding platform integrity and ensuring that system design, change, and configuration do not introduce financial, regulatory, or operational exposure to Treasury. :  System configuration supports business processes accurately  Changes are delivered safely without introducing risk  Integrations operate reliably across all connected systems  System behaviour is consistent and auditable  Release cycles are governed and aligned to Treasury operations The role acts as the technical control layer of the platform, ensuring that all system changes meet both operational and regulatory requirements. Must have the following:  1-2 years' experience 2nd/3rd Line Support capacity in FIS Integrity  Strong configuration and data model knowledge  Strong Treasury business operation understanding  Advanced SQL capability  Integration experience (APIs, SWIFT, SFTP, ERP)  Experience with SaaS release models Desirable  Experience with ATS or equivalent frameworks  Custom reporting and data modelling experience  Exposure to global Treasury implementations Qualifications  Degree in IT, Engineering, or Finance  Vendor certifications preferred This is a hybrid position with 3 days a week in the office in Central London. The salary will be in the range £80K - £100K. Do send your CV to us in Word format along with your salary and notice period.

Role Overview The Data Engineer is responsible for designing, building, and operating scalable, reliable, and secure data pipelines and data platforms that power digital products, analytics use cases, reporting, and data-driven services. Acting as a key contributor within cross-functional delivery teams, the role collaborates closely with Product, Backend, Frontend, Architecture, Data Analytics, and platform teams to deliver trusted data assets across ingestion, transformation, storage, and access layers. At Supervising Associate level, the role leads complex data engineering delivery, sets technical direction and strengthens team capability across initiatives. Key Responsibilities Lead technical delivery across complex data workstreams: Make design decisions and resolve cross-platform dependencies, governance risks, and escalations. Mentor engineers, enforce engineering and data standards, and drive improvements in architecture, quality, lineage, security, observability, cost, and technical debt management. Data Pipeline & Platform Delivery Design, implement, and maintain batch and streaming data pipelines using Python and modern data engineering frameworks. Build reliable ingestion and transformation processes from internal and external data sources, including APIs, databases, files, and events. Develop reusable data processing components and frameworks following software engineering best practices. Data Quality, Reliability & Observability Implement data validation, quality checks, and monitoring to ensure accuracy, completeness, timeliness, and trustworthiness of data. Write clean, testable code with unit and integration tests for data pipelines and processing components. Instrument pipelines with logging, metrics, alerts, and operational monitoring. Performance, Scalability & Architecture Optimize data processing performance, storage layouts, query efficiency, and platform resource usage. Design pipelines for scalability and resilience using retries, idempotency, checkpointing, and backpressure patterns. Apply partitioning, caching, and parallelization strategies where appropriate. Security, Governance & Continuous Improvement Implement secure data handling practices, including access controls, encryption, secrets management, and compliant data processing. Ensure alignment with enterprise, regulatory, privacy, data classification, retention, and lineage requirements. Support audits and data governance processes where required. What success in this role will look like Demonstrates successful leadership of complex data delivery, stronger engineering capability and consistent adoption of platform, quality and governance standards. Reliable delivery and operation of scalable data pipelines and data platform components. Trusted data assets with strong accuracy, completeness, timeliness, and observability controls. Clean, testable, documented, and maintainable Python and SQL-based data engineering solutions. Effective support for incidents, troubleshooting, root-cause analysis, and durable remediation. Provide mentorship and guidance to less experienced team members. Qualifications & Experience Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, Information Technology, or a related field. Professional experience building data pipelines and data platforms using Python. Strong experience with SQL and data modeling concepts, including dimensional, normalized, analytical, or lakehouse patterns. Hands-on experience with relational and analytical data stores, such as PostgreSQL, SQL Server, data warehouses, or data lakes. Experience with CI/CD, automated testing, and code reviews for data workloads. Expertise on cloud platforms, with Azure/Fabric, and relevant data services. Work effectively as part of a team, contributing to collective success while remaining open to feedback and coaching from more experienced colleagues. Strong understanding of data security, access control, observability, and production support practices. 7+ Years of Experience are required.

ContexteDans le cadre de la transition vers une architecture Data Mesh, nous recherchons un(e) Data Product Engineerspécialisé(e) dans le développement de pipelines sur la plateforme Talend Real Time BigData et de data products sur la plateforme Starburst (Trino). La mission consiste à concevoir, collecter, intégrer, construire et opérer des jeux de données fiables, auto-descriptifs et interopérables, en collaboration avec les domain teams et les data owners. MissionsConcevoir des flux de données et des Data Products Développer des pipelines d'intégration de données optimisés via la Talend Data Fabric / Talend Real Time BigData Développer des requêtes SQL optimisées pour Starburst/Trino (push-down predicates, partitionnement, formats de fichiers comme Iceberg/Parquet) Automatiser les pipelines de données (ETL/ELT) avec des outils comme Airflow, dbt, ou Starburst Galaxy Configurer des accès sécurisés (RBAC, row-level security) et des politiques de gouvernance (tagging, lineage) Collaborer avec les domain teams pour identifier les sources de données et les cas d'usage Documenter les data products (métadonnées, ownership, qualité) via des outils comme Amundsen, DataHub, ou Starburst Discover Participer à la définition des standards d'interopérabilité (formats communs, APIs de données) Monitorer la performance (latence, coût des requêtes) et la qualité des données (frais, complétude) Mettre en place des alertes et des dashboards (Grafana, Metabase) pour le suivi des data products Contribuer à l'amélioration continue de la plateforme Starburst (scaling, caching, federation) Compétences techniques requisesTalend RealTime BigData : expérience avancée en développement de pipelines sur Talend Studio en mode batch ou route (runtime) Starburst/Trino : expérience avancée en SQL sur Starburst/Trino (jointures, CTEs, fonctions analytiques) Data Modeling Pipelines : expérience avec Airflow/Astronomer, Spark, Talend Real Time Big Data / Talend Data intégration Stockage : connaissance des formats Iceberg, Parquet, S3 Gouvernance : familiarité avec les outils de sécurité (Ranger, RBAC) DevOps/DataOps : pratiques CI/CD pour les pipelines, infrastructure-as-code (Terraform, Kubernetes) Langages : SQL avancé (mandatory), Python (Pandas, PySpark), bash Compétences transverses (Data Mesh)Compréhension des principes Data Mesh (domain-oriented ownership, self-serve platform, federated governance) Capacité à travailler en mode produit (roadmap, priorisation, collaboration avec les métiers) Sensibilité à la data quality (tests, monitoring, remédiation) et à la documentation (data contracts, métadonnées) Soft SkillsEsprit collaboratif : travail avec les équipes métiers, data scientists, et DevOps Pédagogie : capacité à expliquer des concepts techniques à des non-experts Autonomie : prise d'initiative dans un cadre agile Environnement techniqueExpertise écosystème zoo Hadoop Connaissance / maîtrise Data Connaissance / maîtrise technique de l'environnement DevOps Maîtrise technique de l'environnement Data Expertise couche d'accès et d'échange (Kafka, Nifi, …) Expertise Java, Scala, Python, Hive, Spark Expertise ETL, Bash Expertise SQL / NoSQL