Xcede
Data Engineer (GCP)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer (GCP) with a contract length of "unknown" and an hourly pay rate of "unknown." It requires 5+ years of experience, strong Python and SQL skills, and familiarity with GCP tools. The work location is hybrid in London.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
-
💰 - Day rate
Unknown
-
🗓️ - Date
February 10, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Hybrid
-
📄 - Contract
Outside IR35
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🔒 - Security
Unknown
-
📍 - Location detailed
Greater London, England, United Kingdom
-
🧠 - Skills detailed
#SQL (Structured Query Language) #Data Pipeline #Compliance #Python #Snowflake #Documentation #Databricks #Data Engineering #DataOps #Airflow #Monitoring #"ETL (Extract #Transform #Load)" #Observability #Data Quality #Classification #Data Science #Cloud #GCP (Google Cloud Platform) #Terraform #Infrastructure as Code (IaC) #Spark (Apache Spark) #BigQuery #Scala #Datasets #Data Architecture #Data Governance
Role description
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
What makes you a great fit
• 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: BigQuery, 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 DataOps practices
• Experience building observability for data systems (metrics, alerting, data quality checks, incident response)
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
What makes you a great fit
• 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: BigQuery, 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 DataOps practices
• Experience building observability for data systems (metrics, alerting, data quality checks, incident response)
