Analytics Services Platform Engineer at G-Research

Requirements

Experience running distributed data and analytics systems at scale using tools such as Spark, Kafka, Trino, or Airflow
Strong Linux skills and proficiency in Python for automation and integration
Familiarity with infrastructure as code, using Terraform or Ansible
Deep understanding of AWS analytics technologies including EMR, MSK, Athena, Redshift, Glue, and MWAA
Experience with CI/CD and observability tools such as Jenkins, ArgoCD, Prometheus, Grafana, and OpenTelemetry
Strong problem-solving skills and a systematic approach to diagnosing and resolving issues

Experience with streaming frameworks such as Flink, Kafka Streams, and Kafka Connect
Knowledge of modern data lake technologies including Delta Lake, Iceberg, and Glue Data Catalog
Exposure to DataOps practices and collaboration with Data Engineering teams
Familiarity with GPU-accelerated analytics using Spark with GPUs or RAPIDS
Programming experience with Java, Scala, C#, Python, or Go

Building, operating, and scaling distributed analytics platforms across on-premises and AWS environments
Designing and implementing new platform features that enhance usability, scalability, and the developer experience
Collaborating with research, data, and engineering teams to accelerate time-to-insight through modern analytics solutions
Driving improvements in automation, observability, and resilience across analytics services
Evaluating and adopting emerging technologies such as AI assistants, data mesh, and cloud-native analytics solutions
Defining SLAs, KPIs, and monitoring strategies to ensure reliability, security, and service excellence
Participating in the out-of-hours rota to support critical systems