Data & AI - Data Engineer
CFGI is standing up its Data & AI build team in Singapore and is seeking a hands-on Data Engineer to build and operate the data foundation on which every client artificial-intelligence solution depends.
Roughly eighty per cent of the effort in any artificial-intelligence programme is the data, so this is a central, load-bearing role for an engineer who can design and run governed, audit-ready pipelines that make client data ready for analytics and for artificial intelligence.
This is a Manager-level role based in Singapore, working with the founding Data & AI build team — the artificial-intelligence engineers, data scientists and, as the team grows, the artificial-intelligence architect — as well as CFGI’s APAC and global Data & Analytics and controls practices and client finance, technology and data stakeholders.
The role is hybrid in Singapore, with occasional travel across Asia-Pacific for client work. Work-authorisation sponsorship may be supported where required.
Healthcare and life sciences is the priority market, with delivery extending across CFGI’s other priority sectors — technology and software, real estate and real-estate investment trusts, and industrials — with private equity engaged as a cross-cutting channel rather than a standalone sector.
What you might expect:
Build and operate the data foundation that every client artificial-intelligence and analytics solution runs on.
Design and engineer the ingestion, pipelines, lakehouse, semantic layer, and data-quality and governance controls that turn fragmented client data into authoritative, lineage-traceable, artificial-intelligence-ready data.
Work hand-in-hand with the artificial-intelligence engineers, preparing and serving the data their agents, retrieval systems and models depend on, and build to a client-grade, audit-ready standard from the first engagement.
Design, build and operate data ingestion and integration pipelines from client source systems — enterprise resource planning, customer systems, clinical and operational systems, files and application programming interfaces — into a governed analytics and artificial-intelligence platform, using batch and streaming as required.
Build and maintain the lakehouse or warehouse and its transformation layer, modelling data for both business-intelligence consumers and artificial-intelligence consumers, with tested, version-controlled transformations and clear, documented data models.
Design and maintain a governed semantic layer so that business logic, metrics and definitions are consistent and reusable across dashboards, analytics and artificial-intelligence systems rather than re-implemented and diverging in each.
Prepare and serve artificial-intelligence-ready data for the engineering team — including curated datasets, embeddings source data, feature inputs and retrieval corpora that retrieval-augmented-generation and model builds depend on.
Partner with the artificial-intelligence engineers on