Data Engineer
Data Engineer x2 | GCP | BigQuery | 1 day per week into Central London | £55,000–£60,000
Method Resourcing is proud to partner with a global market-intelligence powerhouse that serves as the strategic hub for the world’s digital infrastructure. They’re investing heavily in their Data platform, monetising high‐value data through subscriptions and market insight products.
This is a genuine growth move, not a back‐fill. The Head of Data has recently stepped up internally and the team is expanding.
They’re hiring two Data Engineers at the same level, sitting in different cost centres, but working closely together day‐to‐day.
The role: This is a data‐engineering‐first role inside a modern GCP‐native environment, with BigQuery at the centre of everything. Python is used, but this is not a Python‐heavy engineering role - the emphasis is much more on how data pipelines are designed, scheduled, deployed, and run reliably in production.
They’re looking for engineers who understand the full lifecycle of data: ingesting it, transforming it, productionising it, and keeping it running cleanly and predictably.
There is some light AI‐driven transformation work already in place (for example, enriching and classifying news content), but this is very much a nice‐to‐have.
What we’re looking for:
- 2-6 years of data engineering experience would be ideal.
- Hands‐on Python experience for cloud data engineering.
- Experience working with GCP or strong transferable cloud experience like AWS.
- Working experience with BigQuery.
- Experience across ETL, data pipelines, and data warehousing.
- Ability to lead pieces of work independently and handle stakeholder requests.
Location: 1 day per week in their central London office
This is well‐suited to solid mid‐level data engineers rather than top‐end specialists.
If this sounds like something you’d like to explore, please apply or contact thomas.morris@methodresourcing.co.uk for more information.
Data Engineer x2 | GCP | BigQuery | 1 day per week into Central London | £55,000–£60,000