Data & Integration Engineer

Saksoft Pte Ltd; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Saksoft Pte Ltd is seeking a Data & Integration Engineer to operate at the intersection of system analysis, enterprise integration, and data engineering. You will support GenAI initiatives by ensuring reliable data movement, transformation, and availability across the ecosystem.

The role requires translating business requirements into data flows, collaborating with multiple teams, and delivering robust data integration solutions to enable AI workflows and knowledge retrieval across

Qualifications

• 5–10 years of experience in system analysis, integration engineering, or data engineering roles.
• Ability to translate requirements into system/data flows and interface specs.
• Experience delivering enterprise integrations with upstream and downstream teams.
• Proficiency with REST APIs, SFTP, batch processing, and data pipeline orchestration.
• Strong SQL and basic to moderate Python for data handling, scripting and troubleshooting.

Responsibilities

• Analyse business and 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.
• Design and implement data movement across systems using APIs, SFTP, batch pipelines, and file transfers.

Skills

Data Engineering

System Integrations

Python

SQL

Java

Tools

Informatica

Cloudera

Git

Jira

Confluence

Control-M

Splunk

OTEL

Job description

Experience: 3-9 Years
Role: Data & Integration Engineer

Key Skills:

• Data Engineering,
• System Integrations,
• Python, SQL, Informatica

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

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

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

Requirements:

Key Requirements

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

• 5-10 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.
• Working experience with Informatica is preferable.

Strong communication skills, with the ability to challenge weak designs and coordinate across business, application, data, infrastructure and security teams.