Description

Architect and maintain scalable data pipelines from Workday to AWS Redshift. You will own the end-to-end data lifecycle, ensuring accuracy, quality, and performance.

Responsibilities

• Design and implement workflows using Airflow to automate data processing.
• Optimize Redshift database performance through query tuning and structural improvements.
• Perform data profiling and analysis to troubleshoot and resolve data-related issues.
• Maintain documented code repositories and configurations using Git and Bitbucket.

Required Skills

• 10+ years of data engineering experience.
• Advanced experience designing AWS data lake solutions.
• Hands-on integration of Redshift with DMS, Glue, Lambda, S3, and Athena.
• Proficiency in Python for developing Airflow DAGs and operators.
• Experience with PySpark and Glue ETL scripting, including data frame transformations and joins.
• Competency in deploying AWS infrastructure via CloudFormation and YAML-defined IAM policies.
• Ability to debug serverless applications using CloudWatch Logs, Log Insights, and CloudTrail.
• Strong understanding of ETL best practices, data modeling, and data integration.
• Expertise in version control using Git.

Preferred Skills

• Experience converting Oracle scripts and stored procedures to Redshift equivalents.
• Proficiency in SQL programming and Redshift stored procedures.

Key Skills

Education

Any Graduate