Description

Develop and maintain ETL pipelines to process data across bronze, silver, and gold layers. Implement data cleansing, validation, and transformation processes to support analytics-ready datasets. Collaborate with the Sr. Data Engineer and Data Architect to ensure alignment with data models. Optimize data workflows to improve processing times and resource utilization.

Responsibilities

• Build ETL pipelines using PySpark and AWS Glue.
• Manage data storage and retrieval in Amazon S3.
• Cleanse and validate data for analytics readiness.
• Optimize workflow performance and resource usage.
• Align data models with architectural standards.

Required Skills

• Bachelor’s degree in Data Engineering, Computer Science, or related field.
• 5+ years of experience in data engineering.
• Proficiency in PySpark and SQL.
• Hands-on experience with AWS Glue and Amazon S3.
• Strong understanding of ETL processes and data warehousing.
• Experience with data analysis and data warehouse concepts.
• Robust problem-solving skills and attention to detail.

Key Skills

Education

Bachelor's degree