Analytics Services Platform Engineer

We tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity. From our London HQ, we unite world-class researchers and engineers in an environment that values deep exploration and methodical execution.As part of our engineering team, you’ll shape the platforms and tools that drive high-impact research - designing systems that scale, accelerate discovery and support innovation across the firm. The role involves designing, building and operating large-scale distributed platforms that power our research, trading and engineering teams across on-premises and AWS environments, using technologies such as Spark, Trino, Kafka, ClickHouse and Airflow.Key ResponsibilitiesBuilding, operating and scaling distributed analytics platforms across on-premises and AWS environmentsDesigning and implementing new platform features that enhance usability, scalability and the developer experienceCollaborating with research, data and engineering teams to

accelerate time-to-insight through modern analytics solutionsDriving improvements in automation, observability and resilience across analytics servicesEvaluating and adopting emerging technologies such as AI assistants, data mesh and cloud-native analytics solutionsDefining SLAs, KPIs and monitoring strategies to ensure reliability, security and service excellenceParticipating in the out-of-hours rota to support critical systemsCore Skills and TechnologiesExperience running distributed data and analytics systems at scale using tools such as Spark, Kafka, Trino or AirflowStrong Linux skills and proficiency in Python for automation and integrationFamiliarity with infrastructure as code, using Terraform or AnsibleDeep understanding of AWS analytics technologies including EMR, MSK, Athena, Redshift, Glue and MWAAExperience with CI/CD and observability tools such as Jenkins, ArgoCD, Prometheus, Grafana and OpenTelemetryStrong problem-solving skills and a systematic approach to diagnosing and

resolving issuesHighly Desirable SkillsExperience with streaming frameworks such as Flink, Kafka Streams and Kafka ConnectKnowledge of modern data lake technologies including Delta Lake, Iceberg and Glue Data CatalogExposure to DataOps practices and collaboration with Data Engineering teamsFamiliarity with GPU-accelerated analytics using Spark with GPUs or RAPIDSProgramming experience with Java, Scala, C#, Python or GoBenefitsHighly competitive compensation plus annual discretionary bonusLunch provided (via Just Eat for Business) and dedicated barista bar35 days’ annual leave9% company pension contributionsInformal dress code and excellent work/life balanceComprehensive healthcare and life assuranceCycle-to-work schemeMonthly company eventsDiversity and InclusionG-Research is committed to cultivating and preserving an inclusive work environment. We want to ensure that applicants receive a recruitment experience that enables them to perform at their best. If you have a disability or special need that requires accommodation please let us know in the relevant section. #J-18808-Ljbffr