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Data Engineer

Laz Partners
London
2 weeks ago
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Role Overview

We have partnered with a fast-growing asset manager looking to hire a Data Engineer with strong analytics experience to join their UK-based investment technology and analytics team. This is a newly created position and the role supports a variety of internal business units, including operations, investment solutions, and reporting functions.


The successful candidate will have2–5 years of experience, withstrong proficiency in Python, a sound understanding of derivatives, and a demonstrated ability to work with business users to deliver practical, data-driven solutions. This is not a modeling or pricing-focused role and is better suited for individuals motivated by problem-solving in production environments rather than purely analytical research.


Key Responsibilities

  • Partner with internal teams to deliver scalable tools that support investment reporting, client communication, and operational workflows.
  • Work on forward-looking cashflow projection systems that help investment professionals assess anticipated fund flows and make strategic decisions.
  • Implement logic and tooling related to fixed income and derivative instruments, ensuring accurate integration of financial characteristics into investment platforms.
  • Build and manage production-ready Python applications, incorporating development best practices including code versioning, testing, and automated deployment workflows.
  • Facilitate the integration of outputs from analytics systems into front-office platforms to enhance portfolio decision-making tools.
  • Maintain proactive communication with cross-departmental stakeholders to understand evolving business needs and translate them into technical deliverables.
  • Utilise visualisation and dashboard tools (such as PowerBI) to enhance user accessibility to quantitative insights and reports


Requirements & Qualifications

  • Bachelor’s or Master’s degree in a quantitative discipline such as Mathematics, Physics, Statistics, Econometrics, or Quantitative Finance.
  • 2–5 years of hands-on experience as a quant developer or analyst within a financial institution.
  • Demonstrable Python experience in a collaborative, version-controlled production environment.
  • Familiarity with financial markets and instruments, especially derivatives and fixed income products.
  • Exposure to systems involving data movement or transformation (ETL processes) is beneficial though not central to the role.
  • Strong verbal and written communication skills, with a track record of collaborating across both technical and non-technical teams.
  • Practical knowledge of PowerBI is advantageous; familiarity with Jupyter Notebooks is helpful but not essential.
  • A personal or professional interest in markets and trading (e.g., independent trading projects) is viewed positively.

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National AI Awards 2025

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