Job Description

Edison Smart is partnering with a growing technology business in the UAE to hire a Real-Time Analytics Engineer.

You’ll join an engineering team building high-performance data infrastructure capable of processing and analysing large volumes of events in real time.

The role will suit someone with strong streaming and distributed systems experience who enjoys solving complex problems around latency, scalability and reliability.

Responsibilities

• Design and build scalable real-time data processing platforms.
• Develop high-throughput, low-latency streaming pipelines.
• Build systems capable of processing and reacting to events in real time.
• Develop data services supporting analytics, automation and intelligent decision-making.
• Work closely with backend and platform engineering teams to integrate real-time data across applications.
• Optimise streaming workloads for performance, reliability and scalability.
• Build monitoring and observability around critical data pipelines.
• Improve fault tolerance and recovery across distributed systems.
• Evaluate new technologies and architectures for real-time processing.
• Take ownership of services from development through to production.

Technical Experience

• Strong experience building real-time or event-driven data systems.
• Hands-on experience with Kafka, Pulsar, Event Hubs or comparable streaming technologies.
• Experience with stream processing technologies such as Spark Streaming, Flink or similar.
• Strong programming skills in Python, Scala or Java.
• Understanding of distributed systems and event-driven architecture.
• Experience designing high-throughput, low-latency data pipelines.
• Knowledge of complex event processing would be advantageous.
• Experience working with time-series or high-volume data stores.
• Strong understanding of production monitoring and observability.
• Experience working with cloud-native environments.

What We're Looking For

You’ll be an engineer who cares about performance, reliability and engineering quality. You should be comfortable working with large-scale data flows, identifying bottlenecks and designing systems where speed and availability are critical.

Experience within high-volume transactional, financial technology, data-intensive or similarly demanding environments would be advantageous.