Data Engineer (SC Cleared)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer (SC Cleared) with a 12-month contract, mostly remote but requires access to London or Bristol. Pay is negotiable, inside IR35. Key skills include Python, SQL, Apache Airflow, AWS, and Kafka.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
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🗓️ - Date discovered
August 7, 2025
🕒 - Project duration
More than 6 months
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🏝️ - Location type
Remote
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📄 - Contract type
Inside IR35
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🔒 - Security clearance
Yes
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📍 - Location detailed
Guildford, England, United Kingdom
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🧠 - Skills detailed
#Airflow #Spark (Apache Spark) #SQL (Structured Query Language) #Apache Airflow #Automated Testing #Schema Design #Cloud #Kafka (Apache Kafka) #Batch #Apache Spark #S3 (Amazon Simple Storage Service) #Compliance #AWS S3 (Amazon Simple Storage Service) #Data Lake #Deployment #Docker #Python #AWS (Amazon Web Services) #DevOps #Security #Version Control #Data Pipeline #Data Engineering #"ETL (Extract #Transform #Load)" #Kubernetes #Data Processing #Big Data #Redshift
Role description
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Job Description
Data Engineer (SC cleared)
Start: ASAP
Duration: 12 months
Location: Mostly Remote - must have access to London or Bristol
Pay: negotiable, INSIDE IR35
Responsibilities
• Design, implement robust ETL/ELT data pipelines using Apache Airflow
• Build ingestion processes from internal systems and APIs, using Kafka, Spark, AWS
• Develop and maintain data lakes and warehouses (AWS S3, Redshift)
• Ensuring governance using automated testing tools
• Collaborate with DevOps to manage CI/CD pipelines for data deployments and ensure version control of DAGs
• Apply best practice in security and compliance
Required Tech Skills
• Python and SQL for processing
• Apache Airflow, writing Airflow DAGs and configuring airflow jobs
• AWS cloud platform and services like S3, Redshift
• Familiarity with big data processing using Apache Spark
• Knowledge of modelling, schema design and partitioning strategies
• Understanding batch Vs streaming data paradigms
• Docker or Kubernetes (containerization)
