Data Engineer — PySpark + AWS Glue

Data Engineer — Py. Spark + AWS Glue ETL & Data Pipelines | 2 Openings Location: Remote (UK) Employment Type: Contract / Permanent Experience Level: 4–8 Years Openings: 2 About the Role We are looking for a skilled Data Engineer with solid hands-on experience in Py. Spark, AWS Glue, and ETL development to build and maintain scalable, production-grade data pipelines on AWS.

You will be part of a delivery-focused team working on complex data engineering challenges, contributing to data lake architecture and end-to-end pipeline development.

Requirements

Key Responsibilities

• Design, develop, and maintain scalable ETL pipelines using Py. Spark and AWS Glue
• Build and optimise data ingestion, transformation, and loading workflows
• Orchestrate data workflows using AWS Step Functions
• Develop serverless functions using AWS Lambda (Python)
• Work with data lake architectures on AWS to support analytical use cases
• Ensure pipeline reliability, monitoring, and performance optimisation Required Skills & Experience
• Strong hands-on experience with Py. Spark and AWS Glue
• Proven track record in ETL pipeline development and optimisation
• Experience orchestrating workflows with AWS Step Functions
• Proficiency in serverless development using AWS Lambda (Python)
• Good SQL skills and a solid understanding of data processing principles Nice to Have
• Exposure to Java-based microservices
• Understanding of REST APIs and backend service integrations
• Experience working with AWS-based data lakes