Description

You will design, build, and configure data applications to meet business process and application requirements.

Responsibilities

• Design and implement data ingestion solutions to create data pipeline architectures.
• Develop and optimize ETL processes using Python and PySpark.
• Build Redshift Spectrum direct transformations and data modeling using S3 data.
• Integrate datasets using AWS Glue, Lambda functions, and Airflow.
• Monitor ETL processes using CloudWatch events.

Required Skills

• 3+ years of big data ETL experience within an AWS environment.
• Proficiency in PySpark for designing, coding, and tuning big data processes.
• Hands-on experience with Python, S3, Lambda, DynamoDB, Athena, and Glue.
• Expert-level skills in writing and optimizing SQL.
• Experience building data platforms using Redshift and RDS.
• Practical knowledge of AWS services including API, CLI, and SDK.
• Experience developing data lakes, cloud data warehouses, and batch or streaming pipelines.
• Ability to design and optimize data models on AWS Cloud.

Preferred Skills

• Expertise in Kinesis and EC2 clusters.
• Experience orchestrating workflows using Airflow.

Key Skills

Education

Any Graduate