Data Architect - Treasury

DeepLight AI is a specialist AI and data consultancy with extensive experience implementing intelligent enterprise systems across multiple industries, with particular depth in financial services and banking. Our team combines deep expertise in data science, statistical modeling, AI/ML technologies, workflow automation, and systems integration with a practical understanding of complex business operations. The Data Architect leads the design and execution of robust, enterprise-grade data architectures that support AI initiatives, advanced analytics, and business intelligence efforts. Operating within client environments with a strong focus on financial services, banking, and treasury domain frameworks, this role translates complex business and regulatory requirements into scalable, secure, and performant data structures. The Data Architect collaborates closely with data engineers, data scientists, and business stakeholders to ensure that foundational data systems align directly with strategic corporate goals. Key Responsibilities Architectural Design & Treasury Data Modeling • Lead the design and implementation of scalable data architectures, enterprise data lakes, and modern warehouse frameworks that address current and future analytical needs • Develop and maintain conceptual, logical, and physical data models (relational, dimensional, NoSQL) to support complex analytics, reporting, and specialized treasury operations (e.g., cash management, liquidity risk, asset-liability management) • Design seamless data flows and integration strategies across core banking, treasury management systems (TMS), external market feeds, and downstream AI/ML pipelines Standards, Governance & Security • Establish data governance, data lineage, quality control standards, and design guidelines that enforce data integrity, security, and auditability • Ensure all data architectures adhere to local and international financial regulatory requirements, data privacy mandates, encryption protocols, and strict access controls Collaboration, Optimization & Innovation • Work closely with data engineers, data analysts, AI specialists, and treasury stakeholders to gather requirements and convert business goals into technical execution • Monitor and optimize database performance, ensuring efficient query execution, low-latency access, partitioning, and indexing strategies across cloud and on-premise platforms • Create and maintain comprehensive documentation covering data models, system topologies, data dictionaries, and architectural guidelines accessible to all organizational levels • Evaluate emerging technologies, cloud capabilities, and data tools to provide data-driven recommendations that elevate the firm's data and AI capabilities Requirements We need you to have: • Strong mastery of data modeling methodologies (relational, dimensional, star/snowflake schemas, Data Vault, NoSQL) and database engines (e.g., PostgreSQL, Oracle, SQL Server, MongoDB) • Deep functional knowledge of modern cloud-based data solutions (Azure, AWS, or GCP), cloud data warehouses (e.g., Snowflake, BigQuery, Synapse), and advanced ETL/ELT orchestration patterns • Solid understanding of data governance principles, metadata management, enterprise data security, and compliance frameworks applicable to financial systems • Excellent communication skills, with a proven ability to explain complex technical designs, data flows, and trade-offs to non-technical stakeholders and executive leadership • Outstanding analytical skills and a structured approach to resolving complex architectural bottlenecks in fast-paced, multidisciplinary team environments • Direct experience working with financial services, corporate treasury operations, banking systems, or financial risk platforms, understanding core treasury concepts such as liquidity, cash positioning, and financial messaging standards • Proven experience operating as a Data Architect or Principal Data Engineer, with a verifiable portfolio of designing and implementing complex, scalable enterprise data architectures • Demonstrated background in designing enterprise-grade data pipelines, integrating disparate real-time and batch data sources into unified analytics architectures • Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Engineering, or a related quantitative discipline (or equivalent practical experience) We'd also like you to have: • Direct hands-on experience integrating major Treasury Management Systems (e.g., FIS Integrity, Murex, Kyriba, SAP Treasury) or financial messaging protocols (e.g., SWIFT, ISO 20022) • Familiarity with data preparation requirements for machine learning models, feature stores, and vector database structures for AI application consumption • Formal industry credentials such as TOGAF, AWS Certified Data Analytics / Solutions Architect, Azure Solutions Architect Expert, or Certified Data Management Professional (CDMP) Benefits The benefits you'll enjoy as part of this role include: • Competitive salary • Comprehensive personal health insurance • Visa Sponsorship for the successful individual • Professional development and certification support • Subscription reimbursement relating to your role • Opportunity to work on cutting-edge AI projects • Monthly Employee Incentive program • Career advancement opportunities in a rapidly growing AI company This position offers a unique opportunity to shape the future of AI implementation while working with a talented team of professionals at the forefront of technological innovation. The successful candidate will play a crucial role in driving our company's success in delivering transformative AI solutions to our clients. At DeepLight AI, we recognise that diversity drives innovation. We are committed to fostering an inclusive environment where individuals with different thinking styles can thrive and contribute their unique strengths to our specialised AI and data solutions. Our goal is to ensure our application and interview process is accessible, predictable, and fair for all candidates. If you require any specific adjustments to the application process, or if you require any reasonable adjustments should you be successful in being processed to the interview stage, please do let us know. This information will be kept strictly confidential and will not impact hiring decisions. Show more Show less

Strong mastery of data modeling methodologies (relational, dimensional, star/snowflake schemas, Data Vault, NoSQL) and database engines (e.g., PostgreSQL, Oracle, SQL Server, MongoDB). Deep functional knowledge of modern cloud-based data solutions (Azure, AWS, or GCP), cloud data warehouses (e.g., Snowflake, BigQuery, Synapse), and advanced ETL/ELT orchestration patterns. Solid understanding of data governance principles, metadata management, enterprise data security, and compliance frameworks applicable to financial systems. Excellent communication skills, with a proven ability to explain complex technical designs, data flows, and trade-offs to non-technical stakeholders and executive leadership. Outstanding analytical skills and a structured approach to resolving complex architectural bottlenecks in fast-paced, multidisciplinary team environments. Direct experience working with financial services, corporate treasury operations, banking systems, or financial risk platforms, understanding core treasury concepts such as liquidity, cash positioning, and financial messaging standards. Proven experience operating as a Data Architect or Principal Data Engineer, with a verifiable portfolio of designing and implementing complex, scalable enterprise data architectures. Demonstrated background in designing enterprise-grade data pipelines, integrating disparate real-time and batch data sources into unified analytics architectures. Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Engineering, or a related quantitative discipline (or equivalent practical experience).

Architectural Design & Treasury Data Modeling: Lead the design and implementation of scalable data architectures, enterprise data lakes, and modern warehouse frameworks that address current and future analytical needs. Develop and maintain conceptual, logical, and physical data models (relational, dimensional, NoSQL) to support complex analytics, reporting, and specialized treasury operations (e.g., cash management, liquidity risk, asset-liability management). Design seamless data flows and integration strategies across core banking, treasury management systems (TMS), external market feeds, and downstream AI/ML pipelines. Standards, Governance & Security: Establish data governance, data lineage, quality control standards, and design guidelines that enforce data integrity, security, and auditability. Ensure all data architectures adhere to local and international financial regulatory requirements, data privacy mandates, encryption protocols, and strict access controls. Collaboration, Optimization & Innovation: Work closely with data engineers, data analysts, AI specialists, and treasury stakeholders to gather requirements and convert business goals into technical execution. Monitor and optimize database performance, ensuring efficient query execution, low-latency access, partitioning, and indexing strategies across cloud and on-premise platforms. Create and maintain comprehensive documentation covering data models, system topologies, data dictionaries, and architectural guidelines accessible to all organizational levels. Evaluate emerging technologies, cloud capabilities, and data tools to provide data-driven recommendations that elevate the firm's data and AI capabilities.