Data Engineer – Real-Time Streaming Systems

Data Engineer – Real-Time Streaming Systems

Overview

🏢 Company | Global trading & technology group

👤 Job | Data Engineer – Real-Time Streaming Systems

🎯 Impact | Low-latency data for decision-making, analytics & automated workflows

📏 Team | Small senior engineering group

🌟 Stack | Azure, Kafka, Snowflake, Python/Scala/Java

📍 Location | London

💻 Hybrid | Office (Hybrid)

💰 Offer | Competitive salary + performance bonus

💎 Benefits | Strong learning budget, certifications, conferences, full health package

The Work

You enjoy building systems where speed and reliability actually matter.

Here, you’ll take fast-moving external feeds, normalise them, and turn them into high-quality real-time datasets used across engineering, analytics and automation. If you like low-latency engineering, repeatable pipelines and being the reason things “just work”, this will suit you.

You’ll get:

• Real ownership over a streaming platform used across the business.
• Direct collaboration with engineers, data teams, and technical end-users.
• A modern environment: Azure, streaming tech, Snowflake, Databricks, CI/CD, TDD.
• Space to influence good engineering habits: automation, observability, data contracts.
• Long-term investment in a growing technology function.

What you’ll be doing

You’ll:

• Build and operate a high-availability, low-latency streaming pipeline.
• Pull external feeds and standardise them into clean, structured datasets.
• Add reliability features: retries, validation, redundancy, graceful failover.
• Apply testing and automation across ingestion, transformation and storage.
• Define APIs, schemas and platform patterns other teams can depend on.
• Build monitoring for latency, quality and system health — and use it to drive improvements.
• Work closely with engineers, data scientists and analysts to wire your data into models and systems.
• Keep the platform documented and continually improved.

You’ll also help steer direction:

• Prioritise data sources that meaningfully improve decision-making and analytics.
• Evaluate new external providers and integrate them safely and at scale.
• Contribute to new data products: curated datasets, feature stores, and real-time decision APIs.

What you’ll bring

You probably have:

• 3+ years in data engineering or real-time systems.
• Experience with high-frequency or event-driven pipelines.
• Strong coding ability in Python, Scala or Java.
• Streaming expertise with Kafka / Confluent.
• Practical experience with Azure (ADLS Gen2, Event Hubs, Databricks/Synapse, Functions, Data Factory, Key Vault).
• Solid experience with Snowflake in production.
• Good engineering fundamentals: tests, CI/CD, automation, version control.

Nice to have:

• Airflow or similar orchestration tools.
• Data quality frameworks (e.g., Great Expectations).
• Terraform/Bicep for IaC.
• Experience in environments where milliseconds and data accuracy matter.

You’re the type who:

• Spots anomalies quickly and goes hunting for root causes.
• Communicates clearly in technical and cross-functional discussions.
• Stays calm under pressure and fixes systems properly, not temporarily.

📅 Interview Process | CV review → Intro call → Technical interview → Team conversations → Offer

If you want to build the backbone of real-time data for a global technology group, hit Apply or send your CV and we’ll set up a confidential chat.