Data Engineer — PySpark + AWS Glue

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