Intern, Site Reliability Engineer – Data Infra (Jan to Apr 2026)

Shopee • Internship • Singapore • 4d ago

Overview

This Site Reliability Engineering (SRE) Internship offers students hands-on exposure to maintaining and improving large-scale data infrastructure systems. As part of the Big Data Infrastructure team, you’ll support real production services while learning how reliability, automation, and monitoring work together in modern engineering environments.

What You'll Get Out of This Internship

Practical experience supporting production-grade big data platforms
Exposure to real SRE practices such as automation, monitoring, and fault prevention
Mentorship from experienced infrastructure and reliability engineers
Strong foundational skills in Linux systems and scripting
Career-relevant experience that supports future roles in SRE, DevOps, or backend engineering

Key Responsibilities

Monitor and support daily operations of large-scale data platforms to ensure system stability
Troubleshoot system issues and help resolve reliability or performance problems
Build and improve automation scripts to reduce manual operational work
Assist with system health checks, log reviews, and incident analysis
Contribute to tools that improve system visibility and operational efficiency
Help document workflows and standard procedures to support team knowledge sharing
Collaborate with engineers to continuously improve platform reliability

Requirements

Currently studying Computer Science, Software Engineering, or a related discipline
Comfortable working with Linux and command-line tools
Basic ability to write and understand shell scripts
Curious about how large systems stay reliable at scale
Willing to learn, ask questions, and take ownership of tasks
Able to work well in a team environment

Who This Internship Is Ideal For

This internship is ideal for students who enjoy working behind the scenes, solving system-level problems, and want exposure to real-world infrastructure engineering.

About the Company

The team operates and scales big data infrastructure that supports critical business and engineering workloads. By focusing on reliability, automation, and observability, they ensure data platforms remain stable, efficient, and ready for growth.