The Rise of Real-Time Data Infrastructure

Posted 4 weeks ago
by Gemma Hall-Peachey
by Gemma Hall-Peachey

Over the past decade, businesses have raced to become more data-driven.  In 2025, being data-driven alone isn’t enough, the real competitive advantage lies in real-time data infrastructure.

Whether it’s fintech companies detecting fraud instantly, retailers personalising offers as customers browse, or AI systems updating on live data streams, organisations can no longer rely on overnight batch processing.  The shift is clear, the future is streaming first architectures, powered by technologies like Apache Kafka, Apache Flink, and Apache Pulsar.

Why Streaming Data is Taking Over

While batch processing still has a role, it’s often too slow for modern business needs. Companies today demand:

  • Low-latency insights: reacting in milliseconds, not hours.
  • Event-driven workflows: responding instantly to customer actions.
  • Scalable and reliable systems: able to handle high-volume, continuous data streams.

That’s why tools like Kafka for event streaming and Flink for real-time analytics have moved from niche technologies to essential infrastructure.  Cloud providers such as AWS Kinesis and Google Pub/Sub are accelerating this trend, making real-time data pipelines easier to deploy at scale.

Key Skills Companies Are Looking For

The move to real-time data isn’t just about technology, it’s about talent.  Hiring managers in data engineering and AI infrastructure are looking for professionals who can:

  • Build low-latency data pipelines: design and operate streaming systems where performance is measured in milliseconds.
  • Understand event-driven architectures: develop systems that respond to live events rather than static datasets.
  • Have hybrid technical skill set: proficiency in Python/SQL, plus Java/Scala for Flink, and sometimes Go/Rust for performance-critical workloads.
  • Deploy cloud-native infrastructure: experience with Kubernetes, Docker, and CI/CD pipelines for scalable real-time systems.
  • Work across disciplines: blend software engineering, DevOps, and data engineering the “full-stack data engineer”.

What This Means for the Hiring Market

The market for streaming data engineers and real-time data infrastructure talent is highly competitive.

Key trends include:

  • Higher salaries.  Specialists in Kafka, Flink, and event-driven design typically earn 5–15% more than batch-only data engineers.
  • High-demand industries.  Fintech, AdTech, e-commerce, logistics, and AI product companies are actively hiring.
  • Geographic hotspots.  Strong demand exists across the UK, US, Germany, and France.

For employers, this means intense competition for top talent.

For candidates, specialising in real-time streaming technologies is a career-defining move.

Takeaways for Teams and Data Engineers

For hiring teams:
Prioritise candidates with production-scale streaming experience, even if they’re rare.

For data engineers:
Invest in mastering Kafka, Flink, and event-driven design to differentiate yourself in a competitive job market.

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For all the sleek minimalism of the cloud, the truth is it’s anything but light and airy. Every “AI-powered” email, every cat video, every model training run lives somewhere — and that somewhere is a data centre, roaring 24/7 with air conditioning, fans, and endless racks of servers devouring electricity like it’s an all-you-can-eat buffet. […]

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