Description

Design and maintain scalable ETL/ELT data pipelines on AWS for analytics and data science use cases.

This role is on-site.

Responsibilities

• Build and optimize data workflows using AWS Glue, ensuring job reliability and performance.
• Design, implement, and manage AWS Redshift data warehousing solutions, including schema design and partitioning.
• Implement data quality checks, validation rules, and monitoring for data accuracy and consistency.
• Collaborate with analytics teams to translate reporting requirements into efficient data models.
• Troubleshoot pipeline issues and improve system reliability, scalability, and governance standards.

Required Skills

• 5+ years of experience in data engineering.
• Deep hands-on expertise with AWS Glue, including job orchestration, Glue Studio, and crawlers.
• Strong experience with AWS Redshift, covering cluster management, query optimization, and workload management.
• Proven track record delivering end-to-end data engineering solutions on AWS.
• Experience implementing data governance, metadata management, and data cataloging.
• Bachelor's degree in a relevant field.
• Ability to mentor junior engineers and communicate technical concepts clearly.

Preferred Skills

• AWS certifications such as Certified Data Analytics, Solutions Architect, or Developer.

Key Skills

Education

Bachelor's degree