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
