Data Engineer; GCP
Job in
Greater London, London, Greater London, W1B, England, UK
Listed on 2026-02-14
Listing for:
Xcede
Full Time
position Listed on 2026-02-14
Job specializations:
-
IT/Tech
Data Engineer, Data Science Manager, Data Security, Data Analyst
Job Description & How to Apply Below
Location: Greater London
GCP Data Engineer –
Hybrid 2/3 days – London –
OUTSIDE IR/35
As a Data Engineer, you’ll design, build, and operate scalable, reliable data pipelines and data infrastructure. Your work will ensure high-quality data is accessible, trusted, and ready for analytics and data science – powering business insights and decision‑making across the company.
What you’ll do- Build and maintain data pipelines for ingestion, transformation, and export across multiple sources and destinations
- Develop and evolve scalable data architecture to meet business and performance requirements
- Partner with analysts and data scientists to deliver curated, analysis‑ready datasets and enable self‑service analytics
- Implement best practices for data quality, testing, monitoring, lineage, and reliability
- Optimise workflows for performance, cost, and scalability (e.g., tuning Spark jobs, query optimisation, partitioning strategies)
- Ensure secure data handling and compliance with relevant data protection standards and internal policies
- Contribute to documentation, standards, and continuous improvement of the data platform and engineering processes
- 5+ years of experience as a Data Engineer, building and maintaining production‑grade pipelines and datasets
- Strong Python and SQL skills with a solid understanding of data structures, performance, and optimisation strategies
- Familiarity with GCP and ecosystem knowledge:
Big Query, Composer, Dataproc, Cloud Run, Dataplex - Hands‑on experience with orchestration (like Airflow, Dagster, Databricks Workflows) and distributed processing in a cloud environment
- Experience with analytical data modelling (star and snowflake schemas), DWH, ETL/ELT patterns, and dimensional concepts
- Experience with data governance concepts: access control, retention, data classification, auditability, and compliance standards
- Familiarity with CI/CD for data pipelines, IaC (Terraform), and/or Data Ops practices
- Experience building observability for data systems (metrics, alerting, data quality checks, incident response)
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