About the Company

Optimum Solutions is an enterprise Digital & IT solutions and services company that engineers digital transformation for enterprises characterized by agility, efficiency and innovation. Founded in 1997, The Company is headquartered in Singapore with 4000+ talented employees across offices and global delivery centers in 9 countries

About the Role

We are seeking an experienced Senior System Analyst / Solution Architect with deep banking domain expertise and a strong track record delivering enterprise data and integration initiatives.

The ideal candidate will operate at the intersection of business, data, systems integration, and AI, translating complex banking requirements into scalable technology solutions while enabling GenAI and Agentic AI use cases across the organization.

This is not a pure development role. The successful candidate will be responsible for analysing business processes, designing end-to-end solution architectures, defining data and integration flows, and ensuring enterprise data is prepared and accessible for AI-driven initiatives.

Key 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.

This is not a pure development role. 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

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)

You are not asking them to build models, just make data usable for them.

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

Mandatory Requirements

Below are the key skillsets that will be required for all relevant tasks mentioned:

10 years of experience in system analysis, integration engineering, data engineering or technical delivery roles.
Strong ability to translate requirements into system flows, data flows, interface specifications and implementation plans.
Experience working with upstream and downstream teams to define and deliver enterprise integrations.
Practical experience with REST APIs, SFTP, batch processing, file based integration and data pipeline orchestration.
Good understanding of data mapping, transformation, aggregation, reconciliation and data quality controls.
Good SQL skills and basic to moderate Python skills for data handling, scripting, automation and troubleshooting.
Exposure to Java
Exposure to Informatica, Cloudera or similar enterprise data platforms.
Working knowledge of Git, branching, pull requests, code reviews and controlled release practices.
Familiarity with CI/CD, Jira, Confluence and enterprise deployment processes.
Experience with Control M or equivalent scheduling tools.
Familiarity with logging (OTEL) and monitoring tools such as Splunk Elastic Stack.
Exposure to GenAI concepts such as document ingestion, RAG, embeddings and data preparation for AI workflows.
Strong communication skills, with the ability to challenge weak designs and coordinate across business, application, data, infrastructure and security teams.

Lead Data and Integration Architect