Cloud Data & AI Platform Engineer

ARGYLL SCOTT CONSULTING PTE. LTD.; Singapore; On-site; SGD 150,000 - 210,000; Full time

Job summary

ARGYLL SCOTT CONSULTING PTE. LTD. is seeking a hands-on Cloud Data & AI Platform Engineer to support the development of enterprise cloud data platforms.

The role focuses on building data pipelines, onboarding business use cases, and implementing cloud platform automation, governance, and cost optimisation capabilities. You will build pipelines across Azure Data Services, Databricks, and Synapse, implement IaC and CI/CD, and collaborate with architects, vendors and MSPs to ensure reliable,

Qualifications

• 5–8 years in Cloud/Data/Platform Engineering or DevOps.
• Hands-on cloud data engineering and data pipelines on cloud platforms.
• Azure experience preferred; Databricks, Synapse or AWS accepted.
• Experience with IaC, CI/CD, governance or FinOps is advantageous.
• MLOps/LLMOps experience is a plus but not required.

Responsibilities

• Build and deploy cloud-based data pipelines using Azure Data Services, Databricks, and Synapse.
• Onboard business units, set up projects, connectivity, and deployment pipelines.
• Implement IaC, CI/CD, automation, and reusable deployment templates.
• Support governance, security controls, compliance automation, and FinOps.
• Collaborate with platform architects, vendors, and MSPs for design and handover.
• Develop reusable engineering patterns to improve reliability, scalability, and self-service.

Skills

Cloud platform engineering

Data pipelines

CI/CD

Infrastructure as Code

Governance & FinOps

MLOps / LLM Ops

Azure

Databricks

Synapse

AWS

Tools

Terraform

GitHub Actions

Azure DevOps

Job description

• Cloud Data & AI Platform Engineer
• Contract: 12 Months | Potential Extension

Role Overview

We are looking for a hands-on Cloud Data & AI Platform Engineer to support the development and implementation of enterprise cloud data platforms. The role focuses on building data pipelines, onboarding business use cases, and implementing cloud platform automation, governance, and cost optimisation capabilities.

Key Responsibilities

• Build and implement cloud-based data pipelines and platform capabilities across Azure Data Services, Databricks, and Synapse.
• Support business divisions with platform onboarding, project setup, connectivity, and deployment pipelines.
• Implement Infrastructure as Code (IaC), CI/CD pipelines, automation, and reusable deployment templates.
• Support cloud governance, security controls, compliance automation, and FinOps initiatives to optimise cloud costs and resource utilisation.
• Work closely with platform architects, vendors, and managed service providers to implement platform designs and ensure smooth operational handover.
• Develop reusable engineering patterns and automation to improve platform reliability, scalability, and self-service capabilities.

Requirements

• 5–8 years of experience in Cloud Engineering, Data Engineering, Platform Engineering, or DevOps.
• Strong hands-on experience in cloud data engineering and implementing data pipelines on cloud platforms.
• Azure experience preferred; candidates with Databricks, Synapse, or AWS experience will also be considered.
• Experience with cloud automation, CI/CD, Infrastructure as Code, governance, or FinOps is advantageous.
• MLOps/LLMOps experience is a plus but not mandatory.
• Strong technical execution, troubleshooting, and collaboration skills.