🛠 Tech Stack

💼 About This Role

You'll design, build, and optimize scalable data pipelines using PySpark and AWS, enabling analytics and AI for enterprise clients. Your work will shape data architecture decisions and drive large-scale data transformation initiatives in a global, collaborative environment.

🎯 What You'll Do

• Build and maintain scalable data pipelines using Python and PySpark
• Optimize data processing architectures on AWS (S3, Glue, EMR, Lambda, Redshift)
• Develop ETL/ELT workflows for large-scale data ingestion and transformation
• Implement data models for Data Lakes and Data Warehouses

📋 Requirements

• Proven experience as a Data Engineer with large-scale data environments
• Strong hands-on experience with Python and PySpark for data pipelines
• Solid experience with AWS data services (S3, Glue, EMR, Lambda, Redshift)
• Advanced SQL skills for querying, modeling, and optimization

✨ Nice to Have

• Familiarity with workflow orchestration tools like Airflow
• English at advanced or fluent level

🎁 Benefits & Perks

• 🏥 Medical assistance fully covered for employee and dependents
• 🍽️ Meal allowance with no salary deduction
• 🏋️ Gympass access for wellness and fitness
• 📈 Employee stock purchase plan with discount
• 👶 Extended maternity and paternity leave

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Call· 30 min
2. 2Technical Screen· 60 min
3. 3Final Interview· 60 min