Analytics Platform Engineer
Europe,
United Kingdom,
London
Permanent
Job ID: 2392
Job Description
[Up to c. £200k Comp Package | Hybrid Working]
Role Overview
We’re partnering with a research-led technology organisation that relies on large-scale analytics to power decision-making across research, trading, and engineering. As data volumes, computational demands, and analytical complexity continue to grow, the firm is investing heavily in shared analytics platforms that can serve many teams reliably and at speed. This role sits within a central platform group responsible for analytics as a service. Rather than building one-off pipelines, you’ll design and operate the core systems that allow researchers and engineers to explore data, run large computations, and derive insights without friction...
Key Responsibilities
- Engineer and operate large-scale analytics services running across on-prem infrastructure and public cloud environments
- Develop and evolve shared analytics platforms that support batch, interactive, and streaming workloads
- Improve developer and researcher experience by standardising access patterns, tooling, and platform interfaces
- Work closely with research and engineering teams to shorten feedback loops and reduce time from data to insight
- Drive automation across deployment, scaling, and recovery workflows to minimise operational overhead
- Strengthen observability, fault tolerance, and capacity planning for business-critical analytics systems
- Assess and introduce new technologies where they meaningfully improve performance, usability, or maintainability
- Define service expectations, operational metrics, and reliability targets for analytics platforms
- Participate in a lightweight on-call rotation supporting core analytics services
What You’ll Bring...
- 4+ years’ experience operating or building distributed analytics or data platforms in production environments
- Solid understanding of cloud-based analytics services, particularly within AWS ecosystems
- Hands-on exposure to large-scale analytics frameworks such as Spark, Trino, Kafka, Airflow, or similar systems
- Strong Linux fundamentals and confidence automating workflows using Python
- Experience with real-time or streaming analytics frameworks
- Practical experience applying Infrastructure-as-Code principles using tools such as Terraform or Ansible
- Familiarity with CI/CD pipelines and modern observability tooling for distributed platforms
- A methodical approach to diagnosing performance, scalability, and reliability issues
- Comfort collaborating directly with research or data-heavy teams in fast-moving environments
- (Preferred) Exposure to modern data lake or table formats used at scale
- (Preferred) Background working alongside Data Engineering or DataOps teams
- (Preferred) Experience with JVM-based or systems programming languages in analytics contexts
...
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