Data & Integration Engineer - GenAI
Posted
Summary
Data & Integration Engineer supporting GenAI initiatives at a Singapore banking and financial services firm: translating requirements into data flows and integration designs, moving data via APIs, SFTP and batch pipelines (Informatica, Cloudera data lake), and preparing structured/unstructured data for AI workflows like RAG. Not a model-building or pure coding role.
About the Client:
Our client is an established
banking and financial services organization in Singapore, the role will be within their technology department .
Responsibilities: We are looking for a
Data & Integration Engineer
who operates effectively at the intersection of
system analysis, enterprise integration and data engineering
to
support GenAI initiatives .
The successful candidate will:
Understand business and functional requirements
Translate them into data flows and integration designs
Work across upstream and downstream systems
Ensure reliable movement, transformation and availability of data for GenAI use cases
Develop scripts / programs to get data from different integration systems
Develop APIs to integrated with relevant systems.
The focus is on
getting data into the right place, in the right format, reliably .
What Matters Most
Strong
system thinking
and ability to understand end to end flows
Ability to
challenge bad designs and propose better ones
Strong
stakeholder communication
Hands on enough to troubleshoot and implement, but not a pure coder
Experience navigating
messy enterprise ecosystems
Key Responsibilities 1. System Analysis & Design
Analyse business/technical requirements and translate them into
data flows and integration designs
Work with upstream and downstream teams to define
data contracts and interfaces
Identify gaps, inefficiencies and risks in current data movement processes
Propose pragmatic solutions balancing speed, quality and maintainability
2. Integration & Data Movement
Design and implement
data movement across systems
using:
APIs
SFTP and file based transfers
Batch pipelines
Coordinate integrations across systems in the DataLake ecosystem (Informatica, Cloudera, etc.)
Ensure data is correctly transformed, mapped and delivered to target systems
Troubleshoot integration issues across environments
3. Data Preparation for GenAI
Support data ingestion and preparation for GenAI use cases:
document ingestion
data aggregation
enrichment and transformation
Work with structured and unstructured data
Ensure data is usable for downstream AI workflows (RAG, search, investigation flows)
4. Delivery & Coordination
Work across multiple teams:
data platforms
application teams
infrastructure
security
Support SIT, UAT and production rollouts
Ensure integration reliability, error handling and monitoring
Document flows, mappings and interfaces clearly
You are not asking them to build models, just make data usable for them.
banking and financial services organization in Singapore, the role will be within their technology department .
Responsibilities: We are looking for a
Data & Integration Engineer
who operates effectively at the intersection of
system analysis, enterprise integration and data engineering
to
support GenAI initiatives .
The successful candidate will:
Understand business and functional requirements
Translate them into data flows and integration designs
Work across upstream and downstream systems
Ensure reliable movement, transformation and availability of data for GenAI use cases
Develop scripts / programs to get data from different integration systems
Develop APIs to integrated with relevant systems.
The focus is on
getting data into the right place, in the right format, reliably .
What Matters Most
Strong
system thinking
and ability to understand end to end flows
Ability to
challenge bad designs and propose better ones
Strong
stakeholder communication
Hands on enough to troubleshoot and implement, but not a pure coder
Experience navigating
messy enterprise ecosystems
Key Responsibilities 1. System Analysis & Design
Analyse business/technical requirements and translate them into
data flows and integration designs
Work with upstream and downstream teams to define
data contracts and interfaces
Identify gaps, inefficiencies and risks in current data movement processes
Propose pragmatic solutions balancing speed, quality and maintainability
2. Integration & Data Movement
Design and implement
data movement across systems
using:
APIs
SFTP and file based transfers
Batch pipelines
Coordinate integrations across systems in the DataLake ecosystem (Informatica, Cloudera, etc.)
Ensure data is correctly transformed, mapped and delivered to target systems
Troubleshoot integration issues across environments
3. Data Preparation for GenAI
Support data ingestion and preparation for GenAI use cases:
document ingestion
data aggregation
enrichment and transformation
Work with structured and unstructured data
Ensure data is usable for downstream AI workflows (RAG, search, investigation flows)
4. Delivery & Coordination
Work across multiple teams:
data platforms
application teams
infrastructure
security
Support SIT, UAT and production rollouts
Ensure integration reliability, error handling and monitoring
Document flows, mappings and interfaces clearly
You are not asking them to build models, just make data usable for them.