Oracle DataStage Developer - ETL (5-6 yrs)

Role Description :

As an Oracle DataStage Developer, you will be a key contributor to our data integration initiatives. You will be responsible for developing ETL jobs, troubleshooting data issues, and ensuring the quality and performance of our data pipelines. Your expertise in Oracle DataStage and your ability to work with complex data transformations will be essential for success in this role.

Responsibilities :

- Design, develop, and maintain ETL jobs using Oracle DataStage.

- Develop complex data transformations and mappings.

- Optimize DataStage jobs for performance and efficiency.

- Implement data quality checks and validation processes.

- Integrate data from various sources, including databases, flat files, and APIs.

- Develop and manage data pipelines for data warehousing and business intelligence.

- Ensure data consistency and accuracy across integrated systems.

- Troubleshoot and resolve data integration issues.

- Perform root cause analysis and implement corrective actions.

- Provide technical support to end-users on data integration processes.

- Collaborate with data architects to design data models and schemas.

- Understand and apply data warehousing concepts.

- Create and maintain technical documentation for DataStage jobs and processes.

- Document data mappings and transformations.

- Develop and execute test plans for DataStage jobs.

- Deploy and monitor DataStage jobs in production environments.

- Identify and resolve performance bottlenecks in DataStage jobs.

- Implement performance tuning strategies.

- Collaborate with cross-functional teams, including data architects, analysts, and developers.

- Communicate effectively with team members and stakeholders.

Qualifications :

Experience :

- Proven experience as an Oracle DataStage Developer.

- Experience in designing, developing, and maintaining ETL processes.

- Strong proficiency in Oracle DataStage (Designer, Director, Administrator).

- Experience with complex data transformations and mappings.

- Understanding of data warehousing concepts.

- Experience with various data sources (databases, flat files, APIs).

- Knowledge of data quality and validation processes.

- Experience with performance tuning and optimization.

- Familiarity with scripting languages (e.g., shell scripting, Python) is a plus.