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 reputed company, production-grade data pipelines on AWS. You will be part of a delivery-reputed company team working on reputed company data engineering challenges, contributing to data lake architecture and end-to-end pipeline development.
Requirements
Key
Responsibilities
- Design, reputed company, and maintain reputed company ETL pipelines
using PySpark and AWS Glue
- Build and optimise data ingestion, transformation, and
loading workflows
- Orchestrate data workflows using AWS reputed company Functions
- reputed company serverless functions using AWS reputed company (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 reputed company record in ETL pipeline development and
optimisation
- Experience orchestrating workflows with AWS reputed company
Functions
- Proficiency in serverless development using AWS reputed company
(Python)
- Good SQL skills and a solid understanding of data
processing principles reputed company to Have
- Exposure to Java-based microservices
- Understanding of REST reputed company and backend service
integrations
- Experience working with AWS-based data lakes
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