Description

Design and build scalable cloud data platforms on AWS, focusing on architecture, data pipelines, and engineering standards.

This role is hybrid.

Responsibilities

• Design AWS cloud architecture for scalable data platforms, covering ingestion, processing, storage, and access patterns.
• Build and optimize data pipelines in Databricks using PySpark for batch and streaming workloads.
• Develop reusable components and standards for modern data engineering platforms, including orchestration, monitoring, and governance.
• Implement data transformations and quality controls to produce reliable, analytics-ready datasets.
• Collaborate with engineering and analytics teams to integrate data sources and support downstream consumption.

Required Skills

• 9-15 years of relevant experience in cloud data engineering and architecture.
• Deep expertise in AWS cloud architecture for data platforms and scalable cloud-based solutions.
• Proficiency in Databricks for building and operating data processing workloads.
• Strong command of PySpark for scalable data transformations and pipeline development.
• Knowledge of modern data engineering platform practices for reliability, performance, and maintainability.

Preferred Skills

• SQL, Python, Apache Spark, and Hadoop.
• Experience with ETL processes.

Key Skills

Education

Any Graduate