Big Data / Data Platform Site Reliability Engineer

Big Data / Data Platform Site Reliability Engineer

We're is partnering with a fast-growing, data-intensive technology organisation to hire a Site Reliability Engineer focused on large-scale data platforms. This role sits at the heart of a mission-critical data environment, with responsibility for reliability, scalability and operational excellence across complex distributed systems.

This is a senior, hands-on role for an engineer who enjoys owning infrastructure, improving system behaviour over time and operating close to production in high-throughput environments.

The role

You’ll be responsible for deploying, configuring, monitoring and maintaining multiple large-scale data stores across distributed environments. Reliability, performance and availability are core to the role, with a strong focus on lifecycle management of critical data infrastructure.

You’ll manage and evolve large Linux-based systems, ensuring predictable performance and high uptime. This includes defining and documenting configuration standards, operational procedures and best practices that support long-term stability.

A key part of the role involves performance and reliability testing, reviewing system configuration, software choices and hardware decisions to identify improvement opportunities. You’ll also play an active role in incident response, root cause analysis and driving lasting reliability improvements across the platform.

There is scope to influence the direction of the technology stack, contributing ideas that improve resilience, observability and operational efficiency.

What we’re looking for

This role suits someone with strong hands-on experience operating large-scale Linux infrastructure in production environments. You should be comfortable owning complex systems and debugging issues across storage, compute and networking layers.

Deep, practical experience with Hadoop-based data platforms is important, including HDFS architecture, security models and operational lifecycle management such as upgrades, scaling and recovery. Experience running Kafka clusters in production environments is also key.

You should have experience designing or improving automation and deployment workflows, with proficiency in scripting or automation using tools such as Python or shell scripting. A solid understanding of networking fundamentals is expected, including TCP/IP, DNS, load balancing and basic network security concepts.

The role requires someone who is comfortable taking technical ownership, contributing to on-call and incident processes, and driving continuous reliability improvement.

The position operates on East Coast US working hours and is suitable for engineers working remotely.

Additional experience

Experience with large-scale analytical query engines, distributed storage systems or high-availability databases is beneficial. Familiarity with observability platforms, configuration management tools, containerisation and Kubernetes in production environments is also valuable.

Engineers who enjoy mentoring others and helping establish operational standards will find opportunities to do so in this role.