Senior IBM DataStage Developer

About the role

UPS is looking for a highly motivated IBM DataStage Developer to join its team in Chennai, India. The role covers designing, developing, implementing and maintaining robust ETL (Extract, Transform, Load) solutions with IBM InfoSphere DataStage, supporting business intelligence and analytics initiatives.

Key responsibilities

• Design, develop and implement ETL processes that extract data from source systems, transform it according to business rules and load it into data warehouses and data marts.
• Develop and maintain DataStage jobs, sequences and workflows, ensuring performance and scalability.
• Troubleshoot data integration issues with data analysts and other stakeholders.
• Write and run complex SQL queries to analyse data, profile sources and validate ETL processes.
• Work with business analysts and data architects to turn data requirements into technical specifications.
• Take part in the full software development lifecycle: requirements, design, development, testing, deployment and documentation.
• Follow data governance policies and monitor ETL processes for performance bottlenecks.
• Contribute to technical documentation such as design specs, mapping documents and operational procedures.

Required profile

• 3 to 5 years of hands-on experience designing, developing and implementing ETL solutions with IBM InfoSphere DataStage.
• Bachelor's degree in Computer Science or equivalent education and work experience.
• Strong understanding of ETL concepts, methodologies and best practices.
• Excellent communication, analytical and problem-solving skills, able to explain technical concepts to technical and non-technical audiences.

Required skills

• Proficiency in complex SQL and relational databases, preferably Oracle.
• Data modelling concepts such as dimensional modelling, star schema and snowflake schema.
• Linux familiarity and basic Linux commands are a plus.
• Preferred: IBM Certified Solution Developer - InfoSphere DataStage certification, exposure to OBIEE or other BI tools, scripting languages such as Shell or Python, cloud data warehousing (Google BigQuery, Azure Synapse), data quality tools and other ETL tools.