Analytics Services Platform Engineer

Talent Acquisition Lead – Technology at G-Research

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 – because the best ideas take time to evolve. Together, we’re building a world-class platform to amplify our teams’ most powerful ideas.

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.

At G-Research, we thrive on innovation and cutting‑edge technology to drive world‑class research and business capabilities. As our operations continue to grow, we’re seeking an experienced Platform Engineer to join our Analytics Services team.

In this role, you’ll help shape the next generation of our analytics infrastructure – designing, building, and operating large‑scale distributed platforms that power our research, trading, and engineering teams. You’ll deliver highly available, secure, and high‑performance analytics services across on‑premises and AWS environments, using technologies such as Spark, Trino, Kafka, Click House, and Airflow.

This is a highly collaborative position, working directly with researchers and engineers to evolve platform capabilities, automate operations, and explore emerging technologies that drive innovation across the business.

• 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

• 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 Open Telemetry
• 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 Data Ops 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
• Highly competitive compensation plus annual discretionary bonus
• Lunch provided (via Just Eat for Business) and dedicated barista bar
• 35 days’ annual leave
• 9% company pension contributions
• Informal dress code and excellent work/life balance
• Comprehensive healthcare and life assurance
• Monthly company events

Not Applicable

Full‑time

Engineering, Information Technology, and Finance

Financial Services and Capital Markets

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