Data-Driven Backend Engineer (Kubernetes, Observability)

Allegis Group Singapore Pte Ltd

Singapore

On-site

SGD 120,000 - 180,000

Full time

6 days ago
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Job summary

Allegis Group Singapore Pte Ltd is seeking a Data & Backend Engineer to design and implement scalable data pipelines and backend services that support high-traffic events. This role focuses on building robust data platforms, ensuring instrumentation, and enabling analytics at scale.

You will design ingestion pipelines, build services, instrument systems for observability, collaborate with data scientists, and migrate toward Kubernetes for scalability and automation.

Qualifications

  • Bachelor's degree in CS/IT or related field.
  • 3+ years of Java, Scala or Python backend/data engineering experience.
  • Experience with distributed data systems (Spark, Kafka, Flink).
  • Knowledge of Kubernetes and containerized deployments.

Responsibilities

  • Design and implement data pipelines for ingestion, transformation, and aggregation.
  • Build backend services to serve data efficiently to internal and external systems.
  • Instrument systems for observability, logging, and monitoring.
  • Collaborate with data scientists to ensure models are properly supported with the right data.
  • Optimize system performance to handle large-scale traffic spikes.
  • Contribute to migration efforts toward Kubernetes for scalability and automation.

Skills

Java
Scala
Python

Education

Bachelor's degree in Computer Science / Information Technology

Tools

Spark
Kafka
Flink
Kubernetes
Prometheus
Grafana
ELK stack

Job description

Allegis Group Singapore Pte Ltd is seeking a Data & Backend Engineer to design and implement scalable data pipelines and backend services that support high-traffic events. This role focuses on building robust data platforms, ensuring instrumentation, and enabling analytics at scale.

You will design ingestion pipelines, build services, instrument systems for observability, collaborate with data scientists, and migrate toward Kubernetes for scalability and automation.

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