Description

Key Skills: AWS Cloud, Pyspark, Databricks, Python, Hadoop, ETL, SQL, Apache Spark

Roles and Responsibilities:

• Design AWS cloud architecture for scalable data platforms, including ingestion, processing, storage, and access patterns.
• Build and optimize data pipelines in Databricks using PySpark for batch and/or 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.

Skills Required:

• 9-15 years of relevant experience in cloud data engineering and architecture
• AWS cloud architecture for data platforms and scalable cloud-based solutions
• Databricks for building and operating data processing workloads
• PySpark for scalable data transformations and pipeline development
• Modern data engineering platform practices for reliability, performance, and maintainability

Good to Have:

• SQL
• Python
• Apache Spark
• Hadoop
• ETL processes

Education: Bachelor's Degree in Computer Science, Master's Degree in Computer Science

Key Skills

Education

Any Graduate