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Senior Data Engineer

Anson McCade
London, United Kingdom
Last month
Applications closed

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Senior Data Engineer


Location: London (Hybrid)

Function: Data Engineering / Data Platform

Salary: Up to £140,000 base + bonus + benefits


About the Role

Our client is a global commodities and energy trading firm operating at the intersection of quantitative research, technology, and trading. Following the recent acquisition of a major energy trading and technology business, the firm has significantly expanded its capabilities in renewable power optimisation, analytics, and physical gas trading across international markets.

They are now hiring a Senior Data Engineer to join their Technology Data, AI & UX team in London.

This team sits close to the trading floor and is responsible for building the data infrastructure that supports traders, quantitative researchers, and data scientists. The work focuses on building scalable pipelines, enabling real-time analytics, and delivering high-quality datasets used for predictive modelling, machine learning, and systematic trading strategies.

This role requires someone who combines strong technical data engineering capability with commercial awareness, capable of working directly with front-office stakeholders and translating trading requirements into robust data solutions.


What You’ll Be Doing

  • Building and maintaining high-performance data pipelines ingesting structured and unstructured datasets from a variety of internal and external sources.
  • Developing ingestion processes including scrapers, ETL pipelines, crawlers, streaming jobs, and services.
  • Cleaning, transforming, and enriching datasets to ensure high quality and usability across analytics and trading use cases.
  • Designing storage solutions across data lakes, databases, and analytical warehouses.
  • Delivering data internally via APIs, Python libraries, and direct database access.
  • Maintaining and optimising existing pipelines and databases used by trading and analytics teams.
  • Supporting data scientists and quantitative teams by enabling access to cloud resources, datasets, and internal Python tooling.
  • Contributing to the automation of post-processing tasks including prediction pipelines and visualisation workflows.
  • Collaborating directly with traders and front-office teams to develop data solutions for real-time analytics and trading decisions.
  • Maintaining documentation and knowledge bases around data sources, architecture, and pipelines.


Ideal Background

The successful candidate will bring strong hands-on data engineering experience and the ability to operate in a front-office, commercially focused environment.

Core experience required:

  • Strong Python development, particularly for data ingestion, crawling, parsing, and transformation.
  • Extensive experience working with SQL and analytical databases, ideally including Amazon Redshift or similar time-series platforms.
  • Experience building production data pipelines in AWS cloud environments.
  • Familiarity with Docker containers and CI/CD pipelines.
  • Experience with Infrastructure as Code and deployment tooling such as CloudFormation or CDK.
  • Strong understanding of data pipeline design, performance optimisation, and data quality practices.
  • Experience working directly with front-office stakeholders such as traders, quants, or analysts.
  • Comfortable operating in agile, fast-paced engineering teams.

Highly desirable experience:

  • Exposure to commodities, energy trading, or financial markets.
  • Experience supporting real-time or near-real-time analytics environments.
  • Knowledge of additional AWS services such as S3, Lambda, Athena, Kinesis, EMR, Fargate, or API Gateway.
  • Experience with big data technologies including Spark, Databricks, Hadoop, or Dask.
  • Familiarity with data visualisation tooling such as Plotly.
  • Experience mentoring junior engineers or leading technical initiatives.


What You’ll Receive

  • Base salary up to £140,000 depending on experience.
  • Participation in a performance-based discretionary bonus scheme.
  • 25 days annual leave plus public holidays.
  • Comprehensive benefits including private medical, dental, life insurance, and strong pension contributions.
  • Access to training and development programmes to support ongoing technical growth.
  • The opportunity to work in a high-performing trading environment where technology directly impacts market decisions.


Who Should Apply

This role will suit a senior data engineer who enjoys operating close to the business, particularly in environments where data directly influences trading or commercial outcomes.

Candidates coming from financial services, trading firms, hedge funds, energy markets, or high-performance data platforms will likely transition most easily, though strong engineers from other real-time data environments will also be considered.


If you are looking to work on complex data challenges, collaborate with front-office teams, and build systems that power real-world trading decisions, this is a strong opportunity.

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