Data & Backend Engineer: Scalable Pipelines & Observability

Allegis Group Singapore Pte Ltd; Singapore; On-site; SGD 110,000 - 170,000; Full time

Job summary

Allegis Group Singapore Pte Ltd is seeking a Data & Backend Engineer in Singapore to design and implement scalable data pipelines and robust backend services that power analytics and operations. The role focuses on building data platforms, instrumentation, and observability to support high-traffic environments.

You will collaborate with data scientists and migrate toward Kubernetes for scalability, reliability, and automation, ensuring data quality and performance across internal systems.

Qualifications

• Bachelor's degree in CS/IT or related field.
• 3+ years in Java, Scala or Python development with backend focus.
• Experience with distributed data systems (Spark, Kafka, Flink, etc.).
• Knowledge of Kubernetes and containerized deployments.
• Familiarity with observability tools (Prometheus, Grafana, ELK stack).
• Strong problem-solving skills and ability to work under time-sensitive conditions.

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 development

Distributed data systems

Kubernetes expertise

Observability tooling familiarity

Education

Bachelor's degree in Computer Science, Information Technology, or related field

Tools

Spark

Kafka

Flink

Prometheus

Grafana

ELK stack

Kubernetes

Job description

Allegis Group Singapore Pte Ltd is seeking a Data & Backend Engineer in Singapore to design and implement scalable data pipelines and robust backend services that power analytics and operations. The role focuses on building data platforms, instrumentation, and observability to support high-traffic environments.

You will collaborate with data scientists and migrate toward Kubernetes for scalability, reliability, and automation, ensuring data quality and performance across internal systems.