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 Apply To This Job