

Square One Resources
Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer with 8+ years of experience, focusing on DBT, Airflow, BigQuery, Python, and SQL. It offers a 6-month hybrid contract in London, with a pay rate of "unknown." Key skills include CI/CD, Terraform, and cloud data engineering.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
Unknown
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🗓️ - Date
August 11, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Hybrid
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📄 - Contract
Fixed Term
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🔒 - Security
Unknown
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📍 - Location detailed
London Area, United Kingdom
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🧠 - Skills detailed
#Deployment #Python #Data Quality #Scala #Security #BigQuery #Terraform #Agile #Macros #Jira #Airflow #GCP (Google Cloud Platform) #Automation #AWS (Amazon Web Services) #dbt (data build tool) #Data Governance #GitHub #SQL (Structured Query Language) #BitBucket #Infrastructure as Code (IaC) #IAM (Identity and Access Management) #Data Engineering #Cloud #Data Pipeline #"ETL (Extract #Transform #Load)" #Monitoring
Role description
Data Engineer – DBT / Airflow / BigQuery
Location: London – Hybrid (3 days per week)
Duration: 6 months, likely to extend to 12 months
Role Overview
We are looking for an experienced Data Engineer to design, build and support scalable data pipelines and analytics-ready data models across GCP and AWS.
The role will focus on DBT, Airflow, BigQuery, Python and SQL, alongside CI/CD, Infrastructure as Code and cloud data engineering.
Key Responsibilities
• Build and maintain DBT Cloud models, transformations, tests, macros, SCDs and deployment processes.
• Design and optimise Airflow DAGs, including scheduling, dependencies, monitoring, retries, idempotency and backfills.
• Develop and optimise BigQuery data pipelines, queries and data models, with a focus on performance and cost.
• Develop robust Python and SQL for data transformation, automation and pipeline development.
• Build and maintain CI/CD and IaC processes using GitHub Actions, Bitbucket, Bamboo, Terraform and/or CloudFormation.
• Support data pipelines and integrations across GCP and AWS.
• Implement data quality, testing, monitoring and production support processes.
• Troubleshoot pipeline and performance issues, including incident response and root-cause analysis.
• Work closely with analytics, product, platform and engineering teams.
Technical Requirements
• Strong hands-on experience with DBT / DBT Cloud, including models, tests, macros, SCDs and release processes.
• Strong Airflow experience, including production DAG development and workflow optimisation.
• Strong BigQuery experience, including performance and cost optimisation.
• Advanced SQL and solid Python development skills.
• Strong data modelling experience across fact/dimension models and SCD patterns.
• Experience with GCP and AWS data environments.
• Experience with CI/CD and Terraform or CloudFormation.
• Understanding of cloud security, IAM, data governance and access controls.
• Experience supporting production data platforms.
Experience
• 8+ years' experience in Data Engineering or a similar technical role.
• Strong problem-solving and troubleshooting skills.
• Excellent communication and stakeholder management.
• Comfortable working independently and across multidisciplinary teams.
• Experience working in Agile environments, with JIRA and Confluence.
Data Engineer – DBT / Airflow / BigQuery
Location: London – Hybrid (3 days per week)
Duration: 6 months, likely to extend to 12 months
Role Overview
We are looking for an experienced Data Engineer to design, build and support scalable data pipelines and analytics-ready data models across GCP and AWS.
The role will focus on DBT, Airflow, BigQuery, Python and SQL, alongside CI/CD, Infrastructure as Code and cloud data engineering.
Key Responsibilities
• Build and maintain DBT Cloud models, transformations, tests, macros, SCDs and deployment processes.
• Design and optimise Airflow DAGs, including scheduling, dependencies, monitoring, retries, idempotency and backfills.
• Develop and optimise BigQuery data pipelines, queries and data models, with a focus on performance and cost.
• Develop robust Python and SQL for data transformation, automation and pipeline development.
• Build and maintain CI/CD and IaC processes using GitHub Actions, Bitbucket, Bamboo, Terraform and/or CloudFormation.
• Support data pipelines and integrations across GCP and AWS.
• Implement data quality, testing, monitoring and production support processes.
• Troubleshoot pipeline and performance issues, including incident response and root-cause analysis.
• Work closely with analytics, product, platform and engineering teams.
Technical Requirements
• Strong hands-on experience with DBT / DBT Cloud, including models, tests, macros, SCDs and release processes.
• Strong Airflow experience, including production DAG development and workflow optimisation.
• Strong BigQuery experience, including performance and cost optimisation.
• Advanced SQL and solid Python development skills.
• Strong data modelling experience across fact/dimension models and SCD patterns.
• Experience with GCP and AWS data environments.
• Experience with CI/CD and Terraform or CloudFormation.
• Understanding of cloud security, IAM, data governance and access controls.
• Experience supporting production data platforms.
Experience
• 8+ years' experience in Data Engineering or a similar technical role.
• Strong problem-solving and troubleshooting skills.
• Excellent communication and stakeholder management.
• Comfortable working independently and across multidisciplinary teams.
• Experience working in Agile environments, with JIRA and Confluence.





