Data Engineer – Quant Finance Pipelines (Remote)

Client Server Ltd.; Greater London; Hybrid; GBP 80,000 - 120,000; Full time

Benefits offered by this job

Work from anywhere 3 weeks per year

Holiday 25 → 30 days

Pension 9%

Healthcare

Cycle to Work

Employee Assistance

Job summary

Client Server Ltd. in London is seeking a Data Engineer (Quant Finance) to join a scaling Investment Research tech company, handling large, complex datasets with an engineering focus.

You will build data pipelines and infrastructure for Quants and Data Scientists, working across the full data lifecycle. The role emphasizes Python/SQL and gradual move into quantitative projects, with hybrid London office work three days per week.

Qualifications

• Commercial Data Engineering or Analyst experience, ideally in market data/finance environment.
• Strong Python and SQL skills with hands-on data pipeline experience.
• Experience building scalable data pipelines and datasets.
• Solid understanding of data modelling and data engineering principles.
• Good academic background with analytical and problem-solving abilities.

Responsibilities

• Build, test and maintain robust data pipelines and data infrastructure.
• Work with large, complex financial datasets.
• Develop data models and improve data quality.
• Create tooling for Quant and Data Science teams.
• Use Python and SQL to implement data solutions.
• Contribute to continuous improvement of data products and processes.
• Progress towards more quantitative responsibilities over time.

Skills

Python

SQL

Data pipelines

Data modelling

Problem solving

Job description

Client Server Ltd. in London is seeking a Data Engineer (Quant Finance) to join a scaling Investment Research tech company, handling large, complex datasets with an engineering focus.

You will build data pipelines and infrastructure for Quants and Data Scientists, working across the full data lifecycle. The role emphasizes Python/SQL and gradual move into quantitative projects, with hybrid London office work three days per week.