Senior DataStage Developer (8 Years)
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Job description
We are seeking a highly experienced and analytical Senior DataStage / ETL Developer with over 8 years of hands-on expertise in designing, developing, and managing enterprise-grade data integration pipelines. In this role, you will lead the implementation of complex ETL/ELT architectures, optimize high-volume data warehouses, and mentor junior developers. The ideal candidate will have deep expertise in the IBM InfoSphere DataStage Suite, strong SQL capability, and a solid understanding of modern data platforms, * Architecture & Design: Analyse complex business requirements and translate them into scalable, end-to-end technical ETL designs and robust data workflows.
- ETL Development: Design, develop, test, and deploy parallel and server jobs using IBM DataStage Designer, utilising advanced stages (Lookup, Join, Merge, Transformer, Aggregator, etc.).
- Job Management & Sequences: Build and manage complex job sequences, execution loops, custom error-handling mechanisms, and standard job routines.
- Performance Tuning: Troubleshoot production bottlenecks and optimize long-running ETL processes, memory allocations, partition strategies, and SQL queries.
- Database & Data Modelling: Create data mappings, target schema structures, and validate complex data logic across databases like Oracle, Terradata, SQL Server, and DB2.
- Automation & Orchestration: Write advanced Unix/Linux shell scripts for automated file handling, pre/post-job processing, and parameter configuration.
- Operations & Scheduling: Oversee enterprise job schedulers (such as Control-M, Auto sys, or Tivoli) to manage dependencies and production runtime.
- Collaboration & Leadership: Partner with Data Architects, Business Analysts, and QA teams to maintain data quality standards. Provide guidance and code reviews for junior team members.
Requirements
- Core Tooling: 8+ years of dedicated experience with IBM InfoSphere DataStage (v11.x preferred) including Designer, Director, Administrator, and QualityStage.
- Databases & Languages: Expert-level proficiency in SQL, PL/SQL, and working knowledge of relational database architectures (RDBMS).
- Data Warehousing: In-depth knowledge of Data Warehousing concepts, Star/Snowflake schemas, and Dimension/Fact loading methodologies.
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