Description

You will design, develop, and maintain scalable ETL/ELT data pipelines on AWS to ingest, transform, and load data from diverse sources.

This role is on-site.

Responsibilities

• Build and optimize data workflows using AWS Glue, ensuring reliability and performance of jobs and crawlers.
• Design and manage data warehousing solutions on AWS Redshift, including schema design, partitioning, and performance tuning.
• Implement data quality checks, validation rules, and monitoring to ensure accuracy and consistency of data assets.
• Collaborate with analytics and business teams to translate reporting requirements into efficient data models.
• Apply security, compliance, and governance best practices across AWS data services, including access control and encryption.

Required Skills

• 5+ years of hands-on experience with AWS Glue, including job orchestration, Glue Studio/Jobs, and integration with other AWS data services.
• Strong experience with AWS Redshift, including cluster management, query optimization, workload management, and cost/performance tuning.
• Proven track record of delivering end-to-end data engineering solutions on AWS for analytics, BI, or data science use cases.
• Experience implementing data governance, metadata management, and data cataloging using AWS-native or similar tools.
• Ability to troubleshoot data pipeline issues, optimize job performance, and proactively improve system reliability.
• Experience contributing to documentation, standards, and reusable frameworks for data engineering on AWS.
• Ability to communicate technical concepts clearly and mentor junior engineers.

Preferred Skills

• AWS-related certification (e.g., AWS Certified Data Analytics, AWS Certified Solutions Architect, or AWS Certified Developer).

Key Skills

Education

Any Gradute