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On-site
Experience
Experienced
About the role
This role sits with a bank's data and AI function, owning the data foundations that support AI, machine learning and agentic applications. You will work alongside data, engineering, AI and platform teams to build scalable, reliable and well-governed data systems. It suits a senior data engineering specialist who enjoys large-scale architecture work and cross-team collaboration.
What you'll do
Shape the bank's AI data architecture and set data engineering standards
Define reusable patterns for ingesting, transforming, enriching, storing and retrieving structured and unstructured data
Contribute to enterprise data standards, semantic modelling frameworks and reusable architecture blueprints
Work with architecture, platform and AI teams to shape the future data ecosystem
Build and run data pipelines for AI, machine learning, analytics and agent-based use cases
Deliver trusted, high-quality datasets for model training, retrieval, feature generation and operational AI workloads
Integrate data across databases, APIs, event streams, cloud platforms, document repositories and external sources
Develop and maintain batch and streaming pipelines using distributed processing technologies
Design and optimise data workflows on lakehouse platforms and distributed compute environments
Build retrieval-ready and feature-ready datasets for AI and machine learning
Develop semantic layers, ontologies, taxonomies and knowledge representations
Design solutions using graph databases, vector stores, document stores and other non-relational technologies
Implement data quality controls, lineage, observability, monitoring and operational support processes
Support ingestion, parsing, chunking, enrichment and normalisation of unstructured and multimodal content
Apply security, governance, privacy and data protection controls across the data lifecycle
Ensure solutions meet enterprise governance, regulatory and operational resilience standards
Maintain documentation, architecture artefacts, engineering standards and operational runbooks
Support architecture reviews and technology governance processes
Uphold the group's values, code of conduct and regulatory compliance expectations
Identify, assess, escalate, mitigate and resolve risk, conduct and compliance matters
Good to know
Based in Singapore
Degree in Computer Science, Engineering, Data Engineering, Information Systems or a related discipline, with equivalent practical experience also valued
Requirements
12+ years in data engineering, software engineering, data platforms or distributed systems
Track record delivering enterprise-scale data solutions
Experience building and operating large-scale batch and streaming pipelines for critical workloads
Strong expertise in Spark, Databricks or similar distributed compute platforms, including tuning and operational support
Experience designing lakehouse architectures with object storage and formats such as Parquet, Delta Lake or Iceberg
Understanding of data modelling and storage technologies including graph, vector, document, key-value and wide-column databases
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