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# Site Reliability Engineer (SRE)

- **Company:** Sparta Commodities
- **Location:** UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Big Data, Continuous Integration, Software Debugging, Programming Tools, Identity and Access Management, Python (Programming Language), PostgreSQL, Performance Tuning, Redis, Reliability Engineering, TypeScript, Datadog, AWS Cdk, Data Logging, Cloud Platform System, Claude Code, Cloudformation, Kotlin, Kubernetes, Low Latency, Apache Flink, Apache Kafka, Terraform, Stream Processing, Amazon Redshift
- **Published:** October 15, 2026
- **Apply:** https://startup.jobs/senior-site-reliability-engineer-sre-sparta-10446297

## About the Role

* 4+ years as a software or reliability engineer, with production systems you've built and supported.
 * High ownership tendencies.
 * Genuine interest in both halves of this role. You want to write the service and own how it runs.
 * Strong in at least one of Kotlin, Java, Python or TypeScript.
 * A solid working understanding of AWS - compute, networking, storage, IAM - from running things in production.
 * Hands-on with infrastructure as code: AWS CDK, Terraform, CloudFormation or similar.
 * Practical experience running container workloads on Kubernetes: deploying, debugging, tuning.
 * Experience with CI/CD tooling and a clear view of a good delivery lifecycle.
 * A habit of instrumenting what you build - metrics, logging, tracing.
 * Experience being on the hook for production, incident response included, and calm when things are on fire.
 * Experience defining or working to service-level objectives, or a clear sense of how you'd start.
 * A strong urge to own and improve things - to spot what isn't working and fix it.
 * Comfortable with agent-based development tools. We use Claude Code; any equivalent is fine.
 * A clear communicator and a pragmatic problem-solver.

NICE TO HAVE EXPERIENCE:

 * Building or operating a platform on Kubernetes, EKS especially.
 * Datadog specifically.
 * Data or streaming systems: Kafka, Flink, Redshift, clustered Postgres.
 * Working to error budgets, and using them to make real prioritisation calls.
 * Security and compliance best practice in cloud environments.
 * Complex distributed environments - high throughput, low latency, large datasets.
 * Any exposure to commodities, energy or financial markets. Useful, but we'll teach you the domain.

## Description

* Design, build and maintain the backend services behind our real-time and analytical data processing.
 * Optimise pipelines and services for low latency, high throughput and scale.
 * Own features end to end, from shaping the approach to running them in production.
 * Contribute to design reviews with a clear view on the trade-offs.

Reliability engineering

 * Own the operational health of your services. Define what healthy means, then measure it.
 * Improve observability, monitoring and alerting in Datadog, so problems surface before a trader notices.
 * Take part in incident response, then close the loop on the root cause.
 * Work with our runtime across Lambda, ECS and EKS, and help move more workloads onto Kubernetes.
 * Help operate the data and streaming infrastructure you depend on: Kafka, Flink, Redis/Valkey, RDS, Redshift.
 * Extend our infrastructure as code in AWS CDK, and our CI/CD pipelines.
 * Reduce toil. Automate the manual, delete the unnecessary, make the next incident less likely., The 'why' is the difference between compliance and conviction. Before we execute, we ask: why does this matter, who does it serve, what changes if we win? People who understand the mission don't need to be managed., 90% of decisions are reversible. Make them, ship, iterate. Perfection is the enemy of efficiency. Bias for action means moving before you have all the answers, but it isn't recklessness. The rule: tell the rest of us what you did, what changed, what you learned.