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Company: 1011 United Overseas Bank Ltd

About UOB

United Overseas Bank Limited (UOB) is a leading bank in Asia with a global network of more than 500 branches and offices in 19 countries and territories in Asia Pacific, Europe and North America. In Asia, we operate through our head office in Singapore and banking subsidiaries in China, Indonesia, Malaysia and Thailand, as well as branches and offices. Our history spans more than 80 years. Over this time, we have been guided by our values – Honorable, Enterprising, United and Committed. This means we always strive to do what is right, build for the future, work as one team and pursue long-term success. It is how we work, consistently, be it towards the company, our colleagues or our customers.

Job Description

Data Management Office (DMO), Innovations Group

DMO is the Group’s enterprise function responsible for the bank’s enterprise big data analytics platform and for driving data monetization across the bank.

Operating within the Innovations Group, DMO enables the bank to unlock value from data by delivering making data easily accessible and discoverable, while ensuring regulatory compliance and control are embedded into how data is accessed and used.

At the same time, DMO is responsible to ensure the enterprise data foundation and platform can evolve with new business demands through identifying new capabilities required and delivering these with our technology partners.

Role Purpose

The Data Innovation & Solutions Analyst is responsible for both building data pipelines and services, and developing AI-driven data agents and applications.

This is a hybrid role (approximately 50% data engineering, 50% AI/agent development) that bridges data platform engineering, metadata/context services, and agentic AI solution delivery.

The role ensures that:

• Data is engineered, accessible, and production-ready, and
• AI agents can effectively consume that data with trusted, governed context

to drive automation, insights, and decision support across the bank.

Key Responsibilities

Data Engineering & Data Services

• Design and build data pipelines and data products (batch and near real-time where applicable) to support business and AI use cases
• Develop and maintain data transformation, ingestion, and processing workflows across the enterprise data platform
• Build and expose data services and APIs to enable consumption by applications and agents
• Ensure data is well-structured, performant, and aligned to domain/data product standards
• Implement and enforce data quality checks, validation rules, and monitoring within pipelines
• Optimize data pipelines for scalability, reliability, and efficiency
• Collaborate with platform and engineering teams to align with enterprise architecture and tooling standards

Agentic Applications & Data Agent Development

• Design and build data management agents (e.g. quality monitoring agents)
• Develop agentic applications for business units (e.g. natural language data discovery, regulatory explainability, data issue triage)
• Translate business problems into agent-based solutions leveraging metadata, APIs, and enterprise data context
• Rapidly prototype, test, and iterate use cases in collaboration with business stakeholders

Data Agent Platform contribution

• Contribute reusable components (e.g. metadata services, context layers, quality signals) to the platform
• Collaborate with engineering teams to industrialize agent capabilities into scalable platform services
• Establish and apply standard design patterns for agent workflows, context management, and governance
• Support onboarding of new domains and use cases onto the data agent platform

AI Context Engineering (Metadata, Quality & Lineage)

• Design and maintain AI-ready context layers, including metadata, business glossary, lineage, and data quality rules
• Engineer context to support retrieval-augmented generation (RAG) and agent-based decision workflows
• Ensure context is well-structured, versioned, traceable, and auditable for regulatory compliance
• Optimize context for accuracy, relevance, and explainability in AI outputs

Agent Orchestration & Integation

• Design and implement agent workflows, including intent handling, context injection, and response generation patterns
• Define and tune prompt strategies, retrieval logic, and confidence signaling mechanisms
• Embed metadata and quality signals into agent execution paths to enhance trust and explainability
• Support testing, validation, and monitoring of agent performance (e.g. accuracy, consistency, auditability)

Stakeholder Enablement  & Use Case Delivery

• Partner with business, engineering, and governance teams to identify and prioritize agent-driven use cases
• Drive adoption of agentic solutions by ensuring they deliver measurable business impact (efficiency, risk reduction, productivity)
• Communicate complex data and AI concepts clearly to both technical and non-technical audiences
• Promote reuse and standardization across use cases and domains

Key Skills & Experience

Mandatory

• 6+ years of experience in data engineering, data platform, or analytics engineering roles in regulated environments
• Strong hands-on experience in:

  Data pipeline development and data processing (SQL, Python or similar)

  Data modelling and data transformation

• Experience building or supporting data services, APIs, or integration layers
• Solid understanding of:

  Data quality, lineage, and metadata concepts

  Enterprise data platforms (e.g. data lake/lakehouse, warehouse)

• Ability to translate business requirements into technical data and solution designs
• Strong analytical mindset: structured, detail-oriented, outcome-driven

Desirable

• Experience with AI/GenAI, RAG architectures, or agent-based solutions
• Familiarity with metadata/catalog tools
• Exposure to API design, integration patterns, or platform-based architecture
• Experience contributing to shared platforms or reusable services
• Prior experience delivering data or AI solutions to business users

Additional Requirements

Develop, Engage, Execute, Strategise

Be a Part of the UOB Family

UOB is an equal opportunity employer. UOB does not discriminate on the basis of a candidate's age, race, gender, color, religion, sexual orientation, physical or mental disability, or other non-merit factors. All employment decisions at UOB are based on business needs, job requirements and qualifications. If you require any assistance or accommodations to be made for the recruitment process, please inform us when you submit your online application.

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