AWS Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AWS Data Engineer on a contract basis, offering a competitive pay rate. Key skills include Python, SQL, AWS services, PySpark, and Terraform. Remote work is available, with a focus on ETL pipeline development and cloud-native architectures.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
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🗓️ - Date discovered
September 26, 2025
🕒 - Project duration
Unknown
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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
#Deployment #Datasets #Agile #Spark (Apache Spark) #Debugging #Data Processing #S3 (Amazon Simple Storage Service) #Snowflake #AWS (Amazon Web Services) #Databricks #"ETL (Extract #Transform #Load)" #ML (Machine Learning) #Lambda (AWS Lambda) #Cloud #Automation #SQL (Structured Query Language) #Python #PySpark #Infrastructure as Code (IaC) #Data Pipeline #Scala #Terraform #Programming #AI (Artificial Intelligence) #Data Science #Data Engineering
Role description
We are seeking a highly skilled AWS Data Engineer to join our team on a contract basis. The successful candidate will design, develop, and maintain scalable data pipelines and platforms, enabling advanced analytics and AI-driven solutions. This is an exciting opportunity to work on cutting-edge projects in a fully remote environment.
Key Responsibilities
• Design, develop, and maintain ETL/ELT pipelines for large-scale structured and unstructured data.
• Build and optimize data solutions using AWS services (S3, Lambda, Glue, Step Functions, EMR).
• Implement scalable data models and warehouses in Postgres and Snowflake.
• Develop distributed data workflows using Databricks and PySpark APIs.
• Write clean, reusable, and efficient Python code for data transformation/orchestration.
• Automate infrastructure provisioning and deployments using Terraform (IaC).
• Collaborate with data scientists, ML engineers, and stakeholders to deliver high-quality datasets.
• Monitor, troubleshoot, and optimize pipelines for performance and reliability.
• Stay updated with emerging trends in data engineering, cloud computing, and AI/LLMs.
Required Skills & Experience
• Strong programming experience in Python with ETL pipeline development.
• Advanced SQL skills; hands-on with Postgres and Snowflake.
• Proven experience with AWS data/compute services (S3, Lambda, Glue, EMR, Step Functions, CloudWatch).
• Proficiency in PySpark and Databricks for distributed data processing.
• Solid experience with Terraform for infrastructure automation.
• Strong understanding of cloud-native architectures and serverless computing.
• Excellent problem-solving, debugging, and performance optimization skills.
• Effective communication and collaboration in fast-paced, agile teams.
We are seeking a highly skilled AWS Data Engineer to join our team on a contract basis. The successful candidate will design, develop, and maintain scalable data pipelines and platforms, enabling advanced analytics and AI-driven solutions. This is an exciting opportunity to work on cutting-edge projects in a fully remote environment.
Key Responsibilities
• Design, develop, and maintain ETL/ELT pipelines for large-scale structured and unstructured data.
• Build and optimize data solutions using AWS services (S3, Lambda, Glue, Step Functions, EMR).
• Implement scalable data models and warehouses in Postgres and Snowflake.
• Develop distributed data workflows using Databricks and PySpark APIs.
• Write clean, reusable, and efficient Python code for data transformation/orchestration.
• Automate infrastructure provisioning and deployments using Terraform (IaC).
• Collaborate with data scientists, ML engineers, and stakeholders to deliver high-quality datasets.
• Monitor, troubleshoot, and optimize pipelines for performance and reliability.
• Stay updated with emerging trends in data engineering, cloud computing, and AI/LLMs.
Required Skills & Experience
• Strong programming experience in Python with ETL pipeline development.
• Advanced SQL skills; hands-on with Postgres and Snowflake.
• Proven experience with AWS data/compute services (S3, Lambda, Glue, EMR, Step Functions, CloudWatch).
• Proficiency in PySpark and Databricks for distributed data processing.
• Solid experience with Terraform for infrastructure automation.
• Strong understanding of cloud-native architectures and serverless computing.
• Excellent problem-solving, debugging, and performance optimization skills.
• Effective communication and collaboration in fast-paced, agile teams.
