Data Engineer PySpark + AWS Glue (Pune)

Data Engineer PySpark + AWS Glue ETL & Data Pipelines | 2 Openings Location: Remote (UK) Employment Type: Contract / Permanent Experience Level: 48 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) Valuable 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 .