Data Operations Engineer

Radley James; Greater London; On-site; GBP 60,000 - 80,000; Full time

Job summary

A premier financial services firm in London is seeking a Data Engineer to serve as a frontline point of contact for traders and internal users. The ideal candidate has over 3 years of experience in data roles and strong Python skills. Responsibilities include managing data quality, developing ETL processes, and implementing data quality checks. This is an excellent opportunity to work in a cutting-edge trading environment.

Qualifications

• 3+ years in Data Engineering, SRE, SWE or Data Ops roles.
• Strong grasp of normalization and API development.
• Experience with lakehouse architectures (Databricks or Delta Lake).

Responsibilities

• Serve as frontline point of contact for data reliability.
• Monitor ingestion pipelines and real-time feeds.
• Develop and maintain ETL/ELT data pipelines.

Skills

Python proficiency

Data modeling

API development

ETL/ELT pipelines

Data quality checks

Tools

Pandas

Spark

Databricks

Job description

One of our clients in the Trading & Market Making space is looking for an engineer to serve as a frontline point of contact for traders, researchers and internal users of data platforms within the London based trading team.

This role sits in the nexus between Data Engineering and Reliability & Operations Engineering, and is an excellent opportunity to work in a dynamic, impactful function within one of the most cutting edge trading environments in the city!

What You'll Do

• Serve as frontline POC for traders, internal users and research teams for everything relating to data reliability.
• Investigate and resolve data quality concerns and freshness anomalies.
• Monitor ingestion pipelines, processes and real time feeds.
• Triaging and addressing alerts promptly to minimize impact on trading.
• Manage relationships with external vendors and resolve upstream issues, specification changes and ensure accurate delivery of datasets.
• Document and relay clear updates to users during production events.

Technical responsibilities

• Ingest, configure and operationalise new datasets.
• Develop and maintain ETL/ELT data pipelines to feed real time trading and research systems.
• Implement data quality checks, anomaly detection and monitoring frameworks.
• Build and maintain high performance API's to expose market and reference data to trading, research and analytics platforms.

Who you are

• 3+ years in Data Engineering, SRE, SWE or Data Ops roles in high performance, time sensitive environments.
• Strong Python proficiency, including exposure to libraries such as Pandas, Arrow, and Spark.
• Strong grasp of data modelling, normalization and API development for large scale analytical or trading systems.
• Experience with lakehouse architectures (Databricks ideally, or Delta Lake).
• Exposure to real time and historical market data within Fixed Income, ETFs or Equities would be excellent.
• Operational instincts - extreme agency and ownership over issues, tackling issues with initiative.