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

- Solid 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

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