DataStage

DataStage

Technology->ETL & Data Quality->IBM Infosphere Datastage->IBM Infosphere Datastage - Datastage • Bachelor’s or Master’s degree (or equivalent) in Engineering/Technology/Computer Applications/Science (e.g., BTech, BE, MCA, MSc, MTech). • 2–5 years of experience in ETL development and support with hands-on expertise in IBM InfoSphere DataStage. • Strong understanding of ETL concepts including extraction, transformation, loading, data validation, and reconciliation. • Experience working with end-to-end ETL lifecycle: development, testing, deployment, and production support. • Ability to analyze job logs, resolve issues, and communicate progress clearly with team members and stakeholders. Preferred Qualifications: • Experience with ETL performance tuning in DataStage (parallelism, partitioning, buffering, and efficient job design patterns). • Familiarity with IBM InfoSphere ecosystem components and best practices for enterprise data integration. • Exposure to data quality checks, audit controls, and building validation frameworks within ETL pipelines. • Experience supporting batch scheduling and operational readiness (restart strategies, alerting, and runbook-driven support). • Ability to work in Agile/iterative delivery models and contribute to continuous improvement of ETL standards and reusable assets. Good to have skills: SQL, Unix/Linux Shell Scripting, Control-M, Informatica, Data Warehousing • Design, develop, and maintain ETL jobs using IBM InfoSphere DataStage to load and transform data across systems. • Translate business and technical requirements into DataStage job designs, mappings, and data transformation logic. • Build and optimize ETL workflows including sequencing, parameterization, reusable job components, and error handling. • Perform unit testing, integration testing, and support UAT by preparing test data and validating outputs against source systems. • Troubleshoot ETL failures, analyze logs, identify root causes, and implement fixes to ensure stable production runs. • Monitor batch schedules and job performance; support improvements in throughput, restartability, and resource usage. • Collaborate with cross-functional teams to ensure data consistency, completeness, and adherence to delivery timelines. • Maintain technical documentation for job designs, data flows, operational runbooks, and deployment notes.