Big Data Platform SRE Engineer

Tencent; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

Tencent Singapore is seeking a hands-on operational engineer to support overseas big data platforms. You will maintain clusters, monitor health, and escalate anomalies under senior guidance.

You will be the first contact for platform usage issues, component errors, and basic performance problems, collaborating with senior engineers to resolve them.

Qualifications

• Some hands-on experience with big data technologies.
• Working knowledge of Hadoop, YARN, Flink, Spark, HDFS, Presto, Hive — plus willingness to go deep on the rest.
• Basic proficiency in Shell and Java / Python / Go.
• Solid Linux/Unix fundamentals: CLI, basic performance observation and log-based troubleshooting.
• A troubleshooting mindset — able to break down problems and iterate.

Responsibilities

• Support day-to-day operation and maintenance of Tencent's overseas big data platforms and clusters under guidance of senior engineers.
• Act as first point of contact for user issues and drive resolutions with senior engineers.

Skills

Big data tech

Java

Python

Go

Shell

Linux

Troubleshooting

Tools

Prometheus

Grafana

ELK

Airflow

Kubernetes

Job description

• Support the day-to-day operation and maintenance of Tencent's overseas big data platforms and clusters under the guidance of senior engineers; Help monitor platform health and **escalate** anomalies.
• Act as a first point of contact for user issues — platform usage, component errors, and basic performance problems — and work with senior engineers to drive them to resolution.
• Participate in reviewing existing operational workflows and standards; identify pain points and contribute improvement ideas.
• Assist in building and maintaining internal operational efficiency tools: capacity management, DevOps pipelines, coverage analytics, automation scripts, and health monitoring.
• Contribute to cluster cost-optimization initiatives, e.g. helping evaluate new technologies or architectures and measuring their impact on processing efficiency and cost.
• Document incidents, resolutions and runbooks to build up the team's shared knowledge base.

What We Look For

Must-have

• Some hands-on experience with big data technologies.
• Working knowledge of at least one of the following: Hadoop, YARN, Flink, Spark, HDFS, Presto, Hive — plus a genuine willingness to go deep on the rest.
• Basic proficiency in Shell and at least one of the following languages: Java / Python / Go.
• Solid Linux/Unix fundamentals: Comfortable on the command line, able to do basic performance observation and log-based troubleshooting.
• A troubleshooting mindset — you can break a problem down, search, ask, and iterate rather than getting stuck.

Nice to have

• Exposure to mainstream big data or cloud data platforms (e.g. Databricks, Snowflake, EMR).
• Coursework or projects in distributed systems, databases, or cloud infrastructure.
• Familiarity with observability tooling (Prometheus, Grafana, ELK) or orchestration/automation (Airflow, Ansible, Kubernetes).
• Any exposure to on-call or production incident handling.