Data & Integration Engineer

SAKSOFT PTE LIMITED; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

SAKSOFT PTE LIMITED is seeking a Data & Integration Engineer to operate at the crossroads of system analysis, enterprise integration and data engineering for GenAI initiatives.

You will translate requirements into data flows, design interfaces, and coordinate across data platforms, applications, security, and infrastructure to ensure reliable data movement and preparation for AI workflows.

Qualifications

• 5–10 years of experience in system analysis, integration engineering, data engineering, or technical delivery roles.
• Proven ability to translate requirements into system and data flows, interfaces, and implementation plans.
• Experience coordinating with upstream and downstream teams to deliver enterprise integrations.
• Hands-on with REST APIs, SFTP, batch processing, and data pipeline orchestration.
• Strong SQL skills and basic to moderate Python for data handling and automation.
• Exposure to Java and enterprise data platforms like Informatica or Cloudera.
• Familiarity with Git, CI/CD, Jira, Confluence, and controlled release practices.
• Experience with logging/monitoring tools (OTEL, Splunk, Elastic Stack).
• Understanding GenAI concepts such as document ingestion, RAG, embeddings, and data prep for AI workflows.

Responsibilities

• 1. System Analysis & Design — Analyse business/technical requirements and translate them into data flows and integration designs; define data contracts and interfaces with upstream and downstream teams; identify gaps, inefficiencies and risks; 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, and batch pipelines; coordinate integrations across DataLake ecosystem (Informatica, Cloudera, etc.); ensure data is transformed, mapped and delivered to target systems; troubleshoot integration issues across environments.
• 3. Data Preparation for GenAI — Support data ingestion, preparation for GenAI use cases (document ingestion, data aggregation, enrichment and transformation); work with structured and unstructured data; ensure data usable for downstream AI workflows (RAG, search, investigation flows).
• 4. Delivery & Coordination — Work across data platforms, application teams, infrastructure and security; support SIT, UAT and production rollouts; ensure integration reliability, error handling and monitoring; document flows, mappings and interfaces clearly.

Skills

Data Engineering

System Integrations

Python

SQL

Informatica

Tools

Informatica

Cloudera

Git

CI/CD

Jira

Confluence

Control-M

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

Key Responsibilities

1. 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. 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. 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. 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.