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