Senior Front Office Data and Analytics Engineer

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Senior Data and Analytics Engineer - Front Office / Fixed Income

£150,000 - £200,000 plus Bonus, excellent benefits and incentive plan

London (City) or Switzerland (if eligible to work there)

Overview

You will work directly with the Front Office investment and trading teams to build, enhance, and support data and analytics infrastructure that powers research, trading, and portfolio decision-making.

This is a hands-on, high-impact role at the core of our front office. You will be expected to take full ownership of your work—from design through production—and to operate with a self-starter mindset in a fast-paced, collaborative environment.

Essential Skills & Experience

• You should have at least 5+ years' experience as a Front Office Engineer (buy-side, sell-side, or trading environment).
• Offer deep expertise in Python, with strong software engineering practices (version control, testing, CI/CD).
• Have a proven track record of building robust data pipelines in cloud-native environments (preferably AWS).
• Experience with Docker and container-based deployments.
• Strong knowledge of Snowflake and NoSQL databases (especially MongoDB).
• Solid understanding of financial markets and instruments particularly Fixed Income (or may consider with an exposure to credit, rates, equities, options, etc.).
• Experience with market data providers (Bloomberg, Refinitiv, etc.) would be useful.
• Any familiarity with tools such as Airflow, Prefect, or other orchestration frameworks would be advantageous.
• Experience building internal tools or dashboards using Dash, Streamlit, or similar web-based data analytics platforms would be nice to have.

Key Responsibilities

• Work closely with portfolio managers, analysts, and traders to understand data and research requirements and build scalable solutions.
• Design, implement, and maintain real-time and batch data pipelines across internal and external sources.
• Manage and optimize data workflows on AWS, including containerized environments using Docker.
• Ingest, transform, and serve large-scale financial datasets across asset classes using Python, Snowflake, and NoSQL databases (e.g., MongoDB).
• Ensure data quality, integrity, and availability across the front office stack.

Networking People (UK) is acting as an Employment Agency in relation to this vacancy.

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Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Information Technology

Industries

• Data Infrastructure and Analytics

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