Data Operations Manager

Data Operations Engineer, Quantitative Trading

Python, C++ & Data Engineering

The Salary - £300,000 to £400,000 annual salary

The Location - London

About the Client

Digital Skills are working with a Global Investment and Fund Management company seeking a highly skilled Data Operations Engineer to join a front-office trading technology environment. The role sits at the heart of large-scale trading data pipelines, processing terabytes of tick data daily on high-performance compute infrastructure.

About the Role

This is a highly technical data engineering opportunity focused on the resilience, automation and performance of business-critical trading data systems. You will build and maintain robust data pipelines, monitoring and alerting capabilities supporting daily model calibration and data generation within a proprietary trading environment.

Responsibilities

• Manage large-scale data pipelines running across high-performance compute infrastructure.
• Build and maintain robust monitoring and alerting systems for critical data pipelines.
• Work with engineering teams to standardise approaches to data monitoring.
• Identify and deliver high-value automation opportunities.
• Improve platform availability, resilience and reliability through testing, standardisation and automation.
• Own and evolve systems, proactively driving technical improvements.
• Apply a systematic and methodical approach to complex problem solving and debugging.
• Collaborate effectively with technical teams across different locations and disciplines.

Desired Skills and Experience

• Expert-level Python and/or C++ engineering experience.
• Deep expertise in data processing, engineering and exploration.
• Experience working in complex AI labs or sophisticated data engineering teams within Tier 1 banks, investment and financial services organisations, or leading technology companies such as Meta, Google or OpenAI, or comparable organisations.
• Strong experience working with large-scale, high-performance data environments.
• Experience with SQL, Pandas, Elasticsearch, Kibana and/or Snowflake.
• Knowledge of containerisation and orchestration technologies including Docker, Kubernetes, Helm and Flux.
• Experience with modern ETL/ELT technologies such as Airflow, Argo, Dagster, Spark or Hive.
• A demonstrable passion for automation and continual improvement.
• Strong focus on system availability and resilience, including testing and standardisation.
• Excellent systematic debugging and problem-solving skills.
• Ability to collaborate effectively across technical teams and geographies.

Summary of the Best Candidate

The strongest candidate will be an accomplished Python/C++ and data engineering specialist who has operated in genuinely complex, data-intensive technical environments. Of particular interest are candidates who have worked within advanced AI labs, Tier 1 banking data teams, major investment or financial organisations, or leading technology businesses such as Meta, Google or OpenAI, or equivalent environments .

You will be comfortable dealing with very large data volumes and production-critical pipelines, with a strong engineering mindset around automation, monitoring, reliability and resilience.

Experience spanning technologies such as Python, C++, SQL, Pandas, Snowflake, Elasticsearch/Kibana, Kubernetes and modern ETL/ELT tooling will be particularly relevant.

This is not simply a traditional data engineering position. The role requires someone capable of working at the intersection of data engineering, high-performance computing, automation and production reliability in a fast-moving front-office technology environment.