SGI

GCP Data Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a GCP Data Engineer with a 6-month contract, offering a pay rate of "XX" per hour. Key skills include 5+ years in Data Engineering, expertise in GCP and DBT, strong SQL, and experience with Python or Spark.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
Unknown
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🗓️ - Date
August 13, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
London Area, United Kingdom
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🧠 - Skills detailed
#Data Quality #Deployment #Security #Storage #BigQuery #GIT #Version Control #Scala #dbt (data build tool) #Documentation #Data Engineering #Data Analysis #GCP (Google Cloud Platform) #Spark (Apache Spark) #Agile #Data Science #Data Pipeline #SQL (Structured Query Language) #"ETL (Extract #Transform #Load)" #Dataflow #Python #Data Processing #Cloud
Role description
We are seeking an experienced GCP Data Engineer to design, build and optimize scalable data solutions on Google Cloud Platform (GCP). The ideal candidate will have strong expertise in modern data warehousing, ETL/ELT development and data transformation using DBT (Data Build Tool). Key Responsibilities: • Design and develop scalable data pipelines using GCP services such as BigQuery, Cloud Storage, Dataflow and Composer. • Build and maintain data transformation models using DBT, ensuring adherence to best practices, testing and documentation. • Develop and optimize ELT processes to ingest, transform, and serve data for analytics and reporting. • Collaborate with data analysts, data scientists and business stakeholders to understand data requirements. • Monitor, troubleshoot, and improve data pipeline performance, reliability and cost efficiency. • Implement data quality, governance and security standards across data platforms. Required Skills & Experience: • 5+ years of experience in Data Engineering. • Strong hands-on experience with Google Cloud Platform (GCP), particularly BigQuery. • Proven expertise in DBT for data modelling, testing and deployment. • Strong SQL skills and experience with data warehousing concepts. • Experience with Python and/or Spark for data processing. • Familiarity with CI/CD practices, version control (Git) and Agile delivery methodologies. • Excellent problem-solving and stakeholder communication skills.