AI Analytics Platform Engineer

Ensign Services; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Ensign Services is seeking a Platforms and Data Engineer to work with data scientists, threat researchers and project managers to develop and manage high‑performance analytics solutions. You will design, deploy and maintain AI analytics platforms and data processing workflows.

You will handle terabytes of data daily, build data lakes and warehouses, monitor operations, and ensure security and scalability across environments.

Qualifications

• Bachelor’s degree in Computer Science/Computer Engineering or equivalent.
• Experience programming Spark, Python, Go, and Bash for data engineering.
• Understanding of Git, GitLab and modern software practices.
• Familiarity with Docker, Kubernetes, and AWS cloud services.

Responsibilities

• Design, develop, deploy and maintain AI analytics platforms and data processing workflows.
• Familiarize with Ensign’s business domain to create data solutions for partners and customers.
• Design, develop, test, deploy operational data transformation processes.
• Design and manage data lake, data warehouse architecture and relational databases.
• Provide monitoring, maintenance and support for data operations across client projects.
• Handle terabytes of data daily and ensure system functionality, health, scalability, resiliency and security.
• Deliver detailed documentation and ensure quality throughout the project lifecycle.

Skills

Spark

Python

Go

Bash

Git

Kubernetes

Docker

AWS

Education

Bachelor's degree in Computer Science/Engineering or equivalent

Tools

GitLab

Kafka

MongoDB

PostgreSQL

Elasticsearch

Kafka

Hadoop

Proxmox

VMware

KVM

Lambda

Glue

Job description

Ensign Services is seeking a Platforms and Data Engineer to work with data scientists, threat researchers and project managers to develop and manage high‑performance analytics solutions. You will design, deploy and maintain AI analytics platforms and data processing workflows.

You will handle terabytes of data daily, build data lakes and warehouses, monitor operations, and ensure security and scalability across environments.