Overview
We are seeking an experienced Senior Data Engineer to join our Data Product Feature Team on a contract basis until December 2026, with the possibility of a six-month extension. This hybrid role will involve collaborating with solution architects and data engineers to deliver scalable, cloud-native data solutions on the Google Cloud Platform (GCP) for a major banking transformation programme.
Responsibilities
- Design and develop scalable data engineering components supporting enterprise key management across GCP-based data products.
- Build pipelines and transformation logic for candidate keys, record matching, merge, cleansing and data standardisation.
- Implement processes for generating and maintaining surrogate keys, deterministic UUIDs and master keys.
- Integrate key generation processes into BigQuery-based data product stores.
- Develop, test and maintain production-grade code supporting data pipelines and reusable engineering components.
- Implement data protection controls including masking, obfuscation, tokenisation and pseudonymisation of sensitive identifiers.
- Collaborate with solution architects, data architects, engineers and platform teams to deliver aligned engineering solutions.
- Support testing and validation across data quality, key generation, interoperability, lineage and operational resilience.
Requirements
- 5+ years of professional Data Engineering experience within enterprise data environments.
- Strong hands-on experience with Google Cloud Platform, particularly BigQuery, Dataflow, Dataproc and Cloud Storage.
- Strong hands-on coding experience, ideally using Python, with the ability to develop, test and maintain production-grade data engineering pipelines and reusable components.
- Experience working within banking or regulated financial services.
- Strong SQL engineering skills and experience developing transformations for large-scale structured datasets.
- Hands-on experience with dbt or a similar transformation framework.
- Understanding of surrogate keys, business keys, deterministic identifiers and data platform key management.
- Experience handling sensitive data using controls such as masking, hashing, tokenisation or pseudonymisation.