Job Description
- Job Description:
- Design and develop complex DataStage jobs (Parallel and Sequence) to extract data from various sources (Flat Files, DB2, SQL Server, APIs) and load them into Netezza
- Optimize DataStage jobs using partitioning, sorting, and buffer tuning
- Perform SQL tuning specifically for Netezza (e.g., managing Distribution Keys, Clustered Base Tables, and minimizing data skew)
- Utilize the Netezza Connector and Netezza Performance Server features within DataStage to implement high-speed data loading (nzload) and external table frameworks
- Write advanced Netezza SQL, including stored procedures, complex joins, and analytical functions to handle data transformation directly within the warehouse (ELT approach)
- Develop Unix/Linux shell scripts to automate job scheduling, file management, and error handling
- Implement data validation and cleansing rules to ensure the integrity and accuracy of the data warehouse
- Provide production support, troubleshoot job failures, and perform root cause analysis for performance bottlenecks
- Requirements:
- Bachelor’s degree in Computer Science, Information Technology, or a related field
- 5-8 years of data engineer experience in ETL Development, with at least 2 years specifically focused on the DataStage-Netezza integration
- Deep understanding of Netezza’s MPP architecture, S-Blades, and FPGA processing
- Proven ability to debug complex data issues and optimize long-running ETL workflows
- Advanced SQL (Netezza-specific SQL), Unix/Linux Shell Scripting
- Knowledge of Star/Snowflake schemas, Dim & Fact tables, and SCD (Type 1/2)
- Control-M or AutoSys (Scheduling), Git/SVN (Version Control), Aginity (Netezza Workbench)
- Nice to have - some experience with Snowflake or Databricks will be preferred.
Benefits:
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