Role Overview

We are looking for a Senior Data Engineer to design, build, and maintain a robust, scalable on-premise data infrastructure.

You will focus on real-time and batch data processing using platforms such as Apache Pulsar and Apache Flink, work with NoSQL databases like MongoDB and ClickHouse, and deploy services using containerization technologies like Docker and Kubernetes.

This role is ideal for engineers with strong systems knowledge, deep backend data experience, and a passion for building efficient, low-latency data pipelines in a non-cloud, on-prem environment.

Key Responsibilities

Data Pipeline & Streaming Development

Design and implement real-time data pipelines using Apache Pulsar and Apache Flink to support mission-critical systems.
Develop high-throughput, low-latency data ingestion and processing workflows across streaming and batch workloads.
Integrate internal systems and external data sources into a unified on-prem data platform.

Data Storage & Modelling

Design efficient data models for MongoDB, ClickHouse, and other on-prem databases to support analytical and operational workloads.
Optimise storage formats, indexing strategies, and partitioning schemes for performance and scalability.

Infrastructure & Containerization

Deploy, manage, and monitor containerised data services using Docker and Kubernetes in on-prem environments.

Performance, Monitoring & Reliability

Monitor the performance of streaming jobs and database queries; fine-tune for efficiency and reliability.
Implement robust logging, metrics, and alerting solutions to ensure data system availability and uptime.
Identify bottlenecks in the pipeline and proactively implement optimisations.

Job Application

We're excited to invite you to apply for a position with us! Please fill out the form to get started on your journey with our team!