Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer on a 6-month contract, remote. Key skills include GCP, BigQuery, advanced SQL, and ETL tools. Requires 3+ years of experience in Data Engineering, CI/CD workflows, and data governance knowledge.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
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🗓️ - Date discovered
September 12, 2025
🕒 - Project duration
More than 6 months
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🏝️ - Location type
Remote
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
United Kingdom
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🧠 - Skills detailed
#"ETL (Extract #Transform #Load)" #Data Pipeline #dbt (data build tool) #DevOps #Data Warehouse #Schema Design #Dataflow #Logging #Looker #Monitoring #Storage #SQL (Structured Query Language) #Automation #Airflow #Observability #Data Modeling #Scala #Data Storage #Datasets #BigQuery #GIT #Terraform #Data Governance #PostgreSQL #GCP (Google Cloud Platform) #Apache Beam #Cloud #Data Quality #Data Engineering #Kafka (Apache Kafka) #BI (Business Intelligence) #ML (Machine Learning)
Role description
We are seeking, on behalf of our client, a highly skilled Data Engineer to support a fast-paced, data-driven project. You will work closely with Cloud/DevOps Engineers to ensure data pipelines are robust, scalable, and seamlessly integrated into a modern GitOps-driven infrastructure.
Responsibilities:
• Design, build, and maintain scalable data pipelines and workflows on GCP.
• Integrate pipelines with BigQuery, PostgreSQL, and other cloud-native services.
• Implement data quality checks, validation frameworks, and monitoring to ensure reliability.
• Collaborate with DevOps team to deploy pipelines using Terraform, ArgoCD, and CI/CD automation.
• Optimize data storage, partitioning, and processing for performance and cost efficiency.
• Support analytics and BI teams by providing clean datasets for tools like Superset, Looker Studio.
• Document workflows, schemas, and processes for long-term maintainability.
Requirements:
• 3+ years of experience in Data Engineering or similar roles.
• Advanced SQL skills and hands-on experience with BigQuery or other MPP data warehouses.
• Proficiency with ETL/ELT tools (dbt, Dataflow, Apache Beam, Airflow, etc.).
• Familiarity with CI/CD workflows, Git, and Infrastructure-as-Code.
• Knowledge of data modeling, schema design, and best practices for cloud data pipelines.
• Understanding of observability (logging, metrics, tracing) and data governance.
• Bonus: experience with streaming data (Pub/Sub, Kafka) or machine learning pipelines.
Contract Details:
• Duration: 6 months (extendable based on project needs)
• Location: Remote
• Engagement: Contract
Why Join Us:
• You will be part of a dynamic project where DevOps and Data Engineering intersect, enabling you to work on cutting-edge cloud infrastructure, influence architectural decisions, and collaborate with a highly skilled technical team.
We are seeking, on behalf of our client, a highly skilled Data Engineer to support a fast-paced, data-driven project. You will work closely with Cloud/DevOps Engineers to ensure data pipelines are robust, scalable, and seamlessly integrated into a modern GitOps-driven infrastructure.
Responsibilities:
• Design, build, and maintain scalable data pipelines and workflows on GCP.
• Integrate pipelines with BigQuery, PostgreSQL, and other cloud-native services.
• Implement data quality checks, validation frameworks, and monitoring to ensure reliability.
• Collaborate with DevOps team to deploy pipelines using Terraform, ArgoCD, and CI/CD automation.
• Optimize data storage, partitioning, and processing for performance and cost efficiency.
• Support analytics and BI teams by providing clean datasets for tools like Superset, Looker Studio.
• Document workflows, schemas, and processes for long-term maintainability.
Requirements:
• 3+ years of experience in Data Engineering or similar roles.
• Advanced SQL skills and hands-on experience with BigQuery or other MPP data warehouses.
• Proficiency with ETL/ELT tools (dbt, Dataflow, Apache Beam, Airflow, etc.).
• Familiarity with CI/CD workflows, Git, and Infrastructure-as-Code.
• Knowledge of data modeling, schema design, and best practices for cloud data pipelines.
• Understanding of observability (logging, metrics, tracing) and data governance.
• Bonus: experience with streaming data (Pub/Sub, Kafka) or machine learning pipelines.
Contract Details:
• Duration: 6 months (extendable based on project needs)
• Location: Remote
• Engagement: Contract
Why Join Us:
• You will be part of a dynamic project where DevOps and Data Engineering intersect, enabling you to work on cutting-edge cloud infrastructure, influence architectural decisions, and collaborate with a highly skilled technical team.
