Description

Design and build scalable AWS cloud data platforms, focusing on ingestion, processing, and storage architectures.

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, 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

• 10+ years of experience in cloud data engineering and architecture.
• Deep expertise in AWS cloud architecture for data platforms and scalable solutions.
• Proficiency in Databricks for building and operating data processing workloads.
• Strong PySpark skills for scalable data transformations and pipeline development.
• Experience with Python and modern data engineering platform practices for reliability and performance.
• Understanding of data governance, monitoring, and orchestration standards.

Preferred Skills

• Experience with Apache Spark, Hadoop, and ETL processes.
• Strong SQL skills for data analysis and manipulation.

Key Skills

Education

Any Graduate