Data Engineer — PySpark + 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 PySpark, 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 PySpark 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 PySpark 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