What are the responsibilities and job description for the Senior Datastage Engineer position at Whiz Global LLC?
Job Description – Sr. DataStage Engineer
Job Title: Sr.
Job Summary
We are seeking an experienced Sr. DataStage Engineer to support enterprise data modernization initiatives. The ideal candidate will have strong expertise in IBM DataStage ETL development, advanced SQL, UNIX/Linux, and shell scripting, with experience modernizing legacy ETL workloads into cloud platforms such as Snowflake and AWS. This role involves collaborating with architects, cloud engineers, and governance teams to build scalable, secure, and high-performance data solutions.
Key Responsibilities
- Design, develop, and maintain enterprise-scale IBM DataStage ETL workflows.
- Build and optimize ETL processes for reliable and high-quality data integration.
- Analyze DataStage job metadata and XML transition logic for legacy modernization.
- Migrate ETL workloads to Snowflake, AWS, or metadata platforms like Collibra.
- Optimize ETL performance using advanced SQL, parallel processing, and shell scripting.
- Develop automation scripts using Bash/Korn Shell (ksh) on UNIX/Linux.
- Collaborate with cloud engineers, architects, and data governance teams.
- Participate in code reviews, testing, deployments, and technical documentation.
- Follow ETL best practices, data quality standards, and enterprise governance policies.
Required Skills
- 6 years of hands-on IBM DataStage development experience.
- Strong experience designing end-to-end ETL workflows.
- Advanced SQL (joins, subqueries, window functions, performance tuning).
- Strong UNIX/Linux administration fundamentals.
- Shell scripting (Bash/Korn Shell) for automation.
- Experience with DataStage metadata and XML transition logic.
- Knowledge of Snowflake and AWS-based data modernization.
- Understanding of data warehousing concepts and ETL best practices.
- Strong troubleshooting, analytical, and communication skills.
Preferred Skills
- Experience with Collibra or other data governance platforms.
- Exposure to AI-assisted development or ETL modernization tools.
- Experience with cloud migration and modernization projects.
- Knowledge of CI/CD and DevOps practices for data engineering.
- Financial services industry experience.