AWS Glue Professional

Job highlights

• Role Summary . We are looking for an experienced AWS Data Engineer with strong hands-on experience in AWS Glue,Python,PySpark / Apache Spark,SQL,and Amazon Redshift.The candidate will be responsible for designing,developing,and maintaining scalable ETL / ELT pipelines and data solutions on AWS Cloud.
• Experience with data quality,governance,and monitoring frameworks
• Good to Have

Role Summary

We are looking for an experienced AWS Data Engineer with strong hands-on experience in AWS Glue, Python, PySpark/Apache Spark, SQL, and Amazon Redshift. The candidate will be responsible for designing, developing, and maintaining scalable ETL/ELT pipelines and data solutions on AWS Cloud.

Roles Responsibilities

• Design and develop scalable ETL/ELT pipelines using AWS Glue, Python, PySpark/Apache Spark, and Java.
• Build and manage AWS Glue Jobs, Crawlers, Triggers, and Workflows.
• Extract, transform, and load data from structured and unstructured sources, including Amazon S3, Aurora, and Redshift.
• Develop scalable data processing workflows for large datasets using Apache Spark.
• Write complex SQL queries and work extensively with Amazon Redshift for data warehousing and analytics.
• Work with AWS services such as Athena and Aurora for data querying and storage.
• Implement serverless data workflows and optimize pipelines for performance and cost efficiency.
• Monitor data pipelines using AWS CloudWatch and troubleshoot failures, data issues, and performance problems.
• Implement data validation, error handling, monitoring, and data quality frameworks.
• Ensure data integrity, governance, security, and compliance with AWS cloud best practices.
• Collaborate with data engineers, analysts, architects, and business stakeholders to understand and deliver data requirements.
• Maintain documentation for data pipelines, architecture, workflows, and operational procedures.
• Ensure adherence to SLAs and contribute to continuous improvement of data engineering processes.

Mandatory Skills

• AWS Glue
• Python
• PySpark / Apache Spark
• SQL
• Amazon Redshift - Mandatory
• AWS Cloud and ETL/ELT development experience

Good to Have

• Apache Airflow
• Java
• AWS Athena
• AWS Aurora
• Amazon S3
• AWS CloudWatch
• Experience with data quality, governance, and monitoring frameworks

Candidate Profile

• 6-8 years of experience in data engineering.
• Strong hands-on experience building and supporting AWS-based data pipelines.
• Good problem-solving, communication, and troubleshooting skills.
• Ability to work with cross-functional teams in a cloud data environment.
• Immediate joiners preferred.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.