Data Engineer - Apache Airflow
Data Engineer / London / Hybrid / Energy Trading
A growing B2B energy supplier operating at the forefront of the UK energy market is investing heavily in its data platform and engineering capability as the business continues to scale its trading operations.
They are looking for a Data Engineer with strong Apache Airflow experience to help design and build the pipelines that power trading, analytics and commercial decision-making.
This is a great opportunity to join a small, highly experienced team where engineers have real ownership of the data platform and the opportunity to work with modern open-source technologies.
What You’ll Be Doing
- Designing and building data pipelines orchestrated with Apache Airflow
- Developing ETL/ELT workflows in Python and SQL to process trading and operational data
- Building reliable, scalable data infrastructure to support analytics and business insight
- Collaborating with analysts, product teams and trading teams to deliver high-value datasets
- Improving data quality, monitoring and pipeline reliability
- Helping shape the future architecture of the data platform
Tech Stack - You don’t need everything here, but experience with some of the following is expected:
- Apache Airflow (core focus)
- Python
- SQL
- Apache Spark or Kafka
- PostgreSQL or similar relational databases
- Docker or containerised environments
- Git and CI/CD workflows
- Data modelling and data warehousing concepts
What They’re Looking For
- Experience building and maintaining data pipelines in production
- Strong Python and SQL skills
- Hands-on experience with Apache Airflow
- Someone who enjoys solving data engineering and infrastructure challenges
- A collaborative engineer comfortable working with both technical and business stakeholders
Why This Role
- Work in a data-driven trading environment
- Join a small team where you can influence architecture
- Build modern data infrastructure from the ground up
- Exposure to energy trading data and real-time market information
Experience:
Typically 2–5 years in Data Engineering or similar roles.