Senior Data Engineer (IBM DataStage & Databricks)

Key Responsibilities

• Design, develop, enhance, and maintain enterprise ETL solutions using IBM DataStage.
• Develop and support Databricks jobs for large-scale data ingestion, transformation, and analytics.
• Write complex SQL and PL/SQL queries, stored procedures, functions, and performance tuning scripts.
• Build scalable and optimized data pipelines for batch and near real-time processing.
• Analyze business requirements and translate them into technical data integration solutions.
• Perform data validation, reconciliation, and troubleshooting to ensure data accuracy and integrity.
• Monitor ETL jobs, identify performance bottlenecks, and implement optimization strategies.
• Collaborate with business analysts, architects, developers, and data stakeholders throughout the SDLC.
• Support production deployments, incident resolution, and ongoing maintenance activities.
• Maintain technical documentation and adhere to enterprise coding and development standards.
• Participate in code reviews and recommend best practices for data engineering and ETL development.

Required Qualifications

• Bachelor''s degree in Computer Science, Information Technology, or a related field.
• 8+ years of experience in Data Engineering or ETL Development.
• Extensive hands-on experience with IBM DataStage for enterprise-scale ETL development.
• Strong expertise in SQL and PL/SQL, including query optimization and performance tuning.
• Experience developing and maintaining Databricks jobs for high-volume data processing and analytics.
• Strong understanding of data warehousing concepts, ETL methodologies, and relational databases.
• Experience troubleshooting complex production data issues.
• Excellent analytical, problem-solving, and communication skills.
• Ability to work independently and collaborate effectively in a cross-functional environment.

Preferred Qualifications

• Working knowledge of Siebel CRM, including its data model and integration touchpoints.
• Experience with enterprise data integration architectures.
• Exposure to cloud platforms such as Azure or AWS.
• Experience with scheduling and orchestration tools.
• Familiarity with Agile/Scrum development methodologies.
• Knowledge of Git or other version control systems.