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Data Operations Engineer Data SRE- Leading High Frequency Trading Firm

External
eFinancialCareers logoEfinancialcareers · London, UK
Full-timeOn-site2w ago
AWSData ModelingPandasPythonSpark
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Requirements

  • 3+ years' experience in a similar role in a high-performance/time-sensitive environment (e.g. Data Engineer, SRE, Software Engineer, Data Operations)
  • Strong proficiency in Python, including libraries such as Pandas, Arrow & Spark
  • Solid understanding of data modeling, normalization, and API development for large-scale analytical or trading systems
  • Experience with Lakehouse architectures (e.g. Delta Lake, Databricks, AWS)
  • Exposure to real-time and historical market data (e.g. fixed income/Credit, ETFs, equities)
  • Rewards and Incentives
  • Great base salaries and industry-leading bonuses
  • Truly flat structure and highly collaborative culture, within a fun, stimulating office environment
  • Generous benefits package, including commuting expenses, breakfast and lunch facilities, regular social activities and more
  • Direct business impact with short feedback loop
  • Whilst we carefully review all applications, to all jobs, due to the high volume of applications we receive it is not possible to respond to those who have not been successful.
  • Contact
  • If you feel you are a strong match for this role, please do not hesitate to get in touch:
  • Dominic Copsey
  • +44 (0)
  • in/dom-copsey-586478143/

Additional Information

Comp: £100-200k This is a fantastic opportunity to work at a tech-focused market maker with groundbreaking success in the high frequency trading space. They're now seeking a motivated data reliability engineer with strong Python skills. You'll join Global Data Engineering in London; a highly talented team with a dedicated focus on supporting the Trading teams. This role offers the opportunity to combine hands-on engineering with high-impact operations. As first-line support for the trading environment, you will be the point of contact for traders, researchers, and other internal users. You can expect a varied workload, including investigating and resolving user issues, addressing data quality concerns, working with vendors and managing alerts. You will also cover integrating new datasets, configuring quality controls, and ensuring pipelines and APIs are robust, scalable, and production-ready. The successful Data Operations Engineer will have outstanding collaboration skills, with strong operational instincts: taking ownership of issues, communicating clearly under pressure and caring deeply about system reliability.


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