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)
- 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

📌 Data Engineer — PySpark + AWS Glue (Pune)
🏢 Yadimen Consulting
📍 Pune