Description

This role defines and drives the architecture of our data platforms.

Responsibilities

• Develop, optimize, and maintain ETL pipelines using AWS Glue.
• Build and manage data workflows and orchestration using Managed Airflow (MWAA).
• Write and optimize SQL and Python/PySpark scripts for data transformation and processing.
• Implement data cataloging and governance using AWS Glue and Lake Formation.
• Monitor, troubleshoot, and optimize data pipelines for performance and reliability.

Required Skills

• 8+ years of experience in data engineering or ETL development.
• Proficiency in AWS data technologies: AWS Glue, Redshift, S3, and Lake Formation.
• Strong programming skills in SQL, Python, and PySpark.
• Experience with data pipeline orchestration using Managed Airflow (MWAA).
• Familiarity with Data Modeling and data warehousing concepts.
• Experience with ETL Development and Data Engineering practices.
• Ability to work within an Agile development environment.
• Strong analytical and problem-solving skills.

Preferred Skills

• Experience with AWS CDK and Build Tools for infrastructure automation.
• Knowledge of data security and governance best practices.

Key Skills

Education

Bachelor's degree