UNITECH
Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Data Engineer contract position lasting over 6 months, based in London/Edinburgh with hybrid remote work. Requires 6+ years of experience, advanced SQL, Python proficiency, AWS, Snowflake, and Terraform skills.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
Unknown
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🗓️ - Date
June 10, 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
#SQL (Structured Query Language) #PySpark #BI (Business Intelligence) #Cloud #IAM (Identity and Access Management) #Apache Airflow #Data Governance #Version Control #Compliance #Pandas #Terraform #"ETL (Extract #Transform #Load)" #S3 (Amazon Simple Storage Service) #AWS (Amazon Web Services) #Data Processing #dbt (data build tool) #SnowPipe #Snowflake #GIT #Microsoft Power BI #Data Warehouse #Data Pipeline #Tableau #Kafka (Apache Kafka) #Python #Data Privacy #Looker #GDPR (General Data Protection Regulation) #Spark (Apache Spark) #Data Engineering #Dimensional Modelling #Airflow #Lambda (AWS Lambda) #Libraries #Schema Design #EC2
Role description
Role Description
This is a Contract/full-time hybrid role for a Data Engineer, based in the London/Edinburgh area, United Kingdom, with the flexibility to work remotely part of the time. The Data Engineer will be responsible for designing, building, and maintaining robust data pipelines and workflows. This includes developing, testing, and optimizing Extract, Transform, Load (ETL) processes, ensuring the integrity and availability of data warehouses, and collaborating with analytics teams to deliver actionable insights from data.
Data Pipeline & Platform Engineering
Cloud Infrastructure (AWS & Terraform)
Data Modelling & Architecture
Collaboration & Delivery
Essential
• 6+ years of hands-on data engineering experience in a professional environment
• Advanced SQL: complex joins, window functions, CTEs, query optimisation
• Proficient Python for data engineering: pandas, PySpark, or similar data processing libraries
• Snowflake: table design, Snowpipe, streams & tasks, performance tuning, RBAC
• AWS: hands-on experience with core services (S3, Glue, Lambda, IAM, EC2/ECS)
• Terraform: writing and maintaining infrastructure-as-code modules for AWS
• Data modelling: dimensional modelling, normalisation/denormalisation, schema design
• Version control: Git branching strategies, pull request workflows
Highly Desirable
• Experience with dbt (data build tool) for transformation layer management
• Familiarity with orchestration tools: Apache Airflow, AWS Step Functions, or Prefect
• Knowledge of streaming/real-time data: Kafka, Kinesis, or similar
• Exposure to data governance, GDPR compliance, or data privacy engineering
Experience with BI tools: Power BI, Tableau, Looker
Role Description
This is a Contract/full-time hybrid role for a Data Engineer, based in the London/Edinburgh area, United Kingdom, with the flexibility to work remotely part of the time. The Data Engineer will be responsible for designing, building, and maintaining robust data pipelines and workflows. This includes developing, testing, and optimizing Extract, Transform, Load (ETL) processes, ensuring the integrity and availability of data warehouses, and collaborating with analytics teams to deliver actionable insights from data.
Data Pipeline & Platform Engineering
Cloud Infrastructure (AWS & Terraform)
Data Modelling & Architecture
Collaboration & Delivery
Essential
• 6+ years of hands-on data engineering experience in a professional environment
• Advanced SQL: complex joins, window functions, CTEs, query optimisation
• Proficient Python for data engineering: pandas, PySpark, or similar data processing libraries
• Snowflake: table design, Snowpipe, streams & tasks, performance tuning, RBAC
• AWS: hands-on experience with core services (S3, Glue, Lambda, IAM, EC2/ECS)
• Terraform: writing and maintaining infrastructure-as-code modules for AWS
• Data modelling: dimensional modelling, normalisation/denormalisation, schema design
• Version control: Git branching strategies, pull request workflows
Highly Desirable
• Experience with dbt (data build tool) for transformation layer management
• Familiarity with orchestration tools: Apache Airflow, AWS Step Functions, or Prefect
• Knowledge of streaming/real-time data: Kafka, Kinesis, or similar
• Exposure to data governance, GDPR compliance, or data privacy engineering
Experience with BI tools: Power BI, Tableau, Looker
