Data Engineer

People Everywhere; Greater London; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

A high-performing trading firm based in London is seeking a motivated Data Engineer to join their team. The role involves shaping how data is ingested and processed, developing resilient ETL systems, and collaborating closely with quants and portfolio managers. Ideal candidates should have expertise in Python, SQL, and Airflow, as well as a strong background in on-premises environments. This is a rare opportunity to have significant ownership and influence in a competitive environment.

Benefits

Competitive compensation package

Private health, vision, and dental insurance

Flexible paid sick leave

Impact-driven environment

Opportunity to work closely with PMs and quants

High level of ownership

Qualifications

• Strong knowledge of Python and SQL.
• Experience working in on-premises environments.
• Hands-on experience with Airflow (or similar orchestration tools).
• Proficiency with Unix/Linux systems.
• Familiarity with relational and NoSQL databases.
• Understanding of data modelling principles.
• Comfortable with Git workflows.

Responsibilities

• Partner with PMs and Quant Developers to translate needs into data pipelines.
• Expand and maintain internal data warehouse.
• Build and optimize ETL workflows using orchestration tools.
• Improve robustness, speed, and scalability of internal data tools.
• Implement monitoring and data quality checks.
• Manage data entitlements and vendor relationships.
• Evaluate and propose tooling for data ingestion.

Education

Bachelor's degree in Computer Science, Engineering, or related technical field

Tools

Python

SQL

Airflow

Unix/Linux

Postgres

MongoDB

Git

Job description

We are looking for a highly motivated Data Engineer to join a small and growing team at a high-performing trading firm. This role is ideal for those who want to see tangible impact from their work. You will be collaborating directly with quants and portfolio managers to architect data flows and build resilient ETL systems that power real-time decision-making.

This is not a back-office or purely maintenance role. You will help shape how the firm ingests, processes, and leverages data across multiple strategies. The position offers significant ownership and influence for engineers who enjoy seeing the direct results of their technical contributions. This is a rare opportunity.

We are especially interested in candidates who prefer working on-premises infrastructure, value clarity and performance in their code, and have strong instincts around data reliability and system orchestration.

Tech Stack

Python, SQL, Airflow, Unix/Linux, Postgres, MongoDB, on-premises infrastructure, Git, data warehousing, data modelling.

Location

London, UK (hybrid format, with a requirement of 3 days per week in the office).

Benefits

• Competitive, market-leading compensation package (aligned with top-tier trading firms);
• Private health, vision, and dental insurance;
• Flexible paid sick leave;
• Impact-driven environment where contributions are visible and valued;
• The opportunity to work closely with PMs, quants, and senior engineering leadership;
• High level of ownership and the ability to directly influence data architecture and strategy.

Qualifications

• Strong knowledge of Python and SQL;
• Experience working inon-premisesenvironments(cloud not required or preferred);
• Hands-on experience with Airflow (or similar orchestration tools);
• Proficiency with Unix/Linux systems;
• Familiarity with relational and NoSQL databases (Postgres, MongoDB, etc.);
• Understanding of data modelling principles and trade-offs (normalisation vs denormalisation);
• Comfortable with Git workflows and collaborative engineering environments;
• Bachelor's degree in Computer Science, Engineering, or related technical field.

Responsibilities

• Partner with PMs and Quant Developers to translate trading and research needs into reliable data pipelines;
• Expand and maintain the internal data warehouse;
• Build and optimise ETL workflows using orchestration tools (Airflow preferred);
• Improve robustness, speed, and scalability of internal data tools;
• Implement monitoring, anomaly detection, and data quality checks;
• Manage data entitlements and vendor relationships;
• Evaluate and propose tooling for data ingestion, streaming, and management.

Nice to have

• Experience working in fast-paced tech or financial environments;
• Background in data engineering for trading or analytics products;
• Java skills are a bonus;
• Familiarity with Hadoop or other on-prem data solutions;
• Master's degree in a quantitative or technical field.

If this sounds like the kind of environment where you do your best work, we would love to meet you.