Job Summary :

We are looking for an experienced IBM InfoSphere DataStage Developer with strong expertise in ETL development, data integration, transformation, and performance tuning. The candidate should have hands-on experience developing and supporting DataStage jobs and working with large-volume data environments.

Key Responsibilities :

- Design, develop, test, and maintain ETL workflows using IBM InfoSphere DataStage.

- Develop and maintain Parallel Jobs, Server Jobs, and Sequence Jobs.

- Work with DataStage file, processing, database, and debugging stages.

- Develop complex ETL mappings, transformations, validations, and business logic.

- Configure and manage DataStage parameters, parameter sets, environment variables, and job sequences.

- Develop Execute Command activities and Unix/Linux shell scripts for automation and ETL processing.

- Schedule, monitor, troubleshoot, and support ETL jobs in development and production environments.

- Perform ETL performance tuning and optimization for high-volume data processing.

- Work with SQL and databases including DB2, Teradata, and Snowflake.

- Perform source-to-target mapping, data validation, reconciliation, and data quality checks.

- Troubleshoot job failures, data issues, and performance bottlenecks.

- Ensure ETL solutions are scalable, reliable, and aligned with business and technical requirements.

Must-Have Skills :

- Strong hands-on experience with IBM InfoSphere DataStage.

- Good knowledge of Parallel, Server, and Sequence Jobs.

- Strong understanding of DataStage stages and transformation logic.

- Experience developing complex ETL mappings and workflows.

- Strong knowledge of parameters, parameter sets, environment variables, and job sequences.

- Good experience with SQL and database connectivity.

- Hands-on experience with Unix/Linux shell scripting.

- Experience in job scheduling, monitoring, debugging, troubleshooting, and performance tuning.

- Experience handling large-volume data and optimizing ETL jobs.

- Strong understanding of source-to-target mapping, data validation, reconciliation, and data quality.

Good to Have :

- Experience with Snowflake or other cloud data platforms.

- Exposure to data warehousing and data integration projects.

- Experience with production support and enterprise-scale ETL environments.

- Knowledge of ETL best practices, data governance, and data quality frameworks.