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À propos
Key responsibilities • Design, develop, and maintain IBM DataStage ETL jobs that ingest file feeds (CSV, fixed-width, delimited) and load curated destination tables in SQL Server. • Build end-to-end ETL flows, including staging, transformations, validations, and publishing to downstream schemas. • Perform source-to-target mapping and implement transformation logic based on business and technical requirements. • Use common DataStage stages and patterns (e.g., Sequential File, Transformer, Lookup, Join/Merge, Aggregator, Sort, Funnel, Remove Duplicates), with attention to partitioning and parallel job design. • Write, optimize, and tune SQL Server queries, stored procedures, and T SQL scripts used in ETL workflows. • Implement restartable and supportable jobs: parameterization, robust logging, reject handling, auditing columns, and reconciliation checks. • pply data quality controls (format checks, referential checks, null/duplicate checks, threshold checks) and produce clear exception outputs for remediation. • Monitor and troubleshoot ETL runs using DataStage Director/Operations Console and SQL Server tooling; perform root-cause analysis and fix defects. • Improve performance through job design tuning (partitioning strategy, sorting choices, buffering, pushdown where appropriate) and SQL tuning (indexes, statistics, set-based logic). • Participate in code reviews, testing, documentation, and release activities; maintain clear runbooks and operational procedures. • Collaborate with business analysts, data modelers, QA, and production support to deliver stable pipelines. Required skills and experience • Hands-on IBM DataStage ETL development experience, including data mapping and transformation implementation. • Strong SQL Server experience with advanced T SQL (joins, window functions, CTEs, temp tables, indexing basics, query plans). • Solid understanding of file-based ingestion and parsing (CSV, fixed-width, headers/trailers, control totals, encoding, delimiters, quoting/escaping). • Experience designing ETL jobs with good operational characteristics: parameter-driven design, logging, error handling, restart/re-run strategy, and auditability. • bility to troubleshoot data issues end-to-end (source file → stage tables → target tables) and communicate findings clearly. Preferred qualifications • Experience with DataStage Parallel Jobs tuning (partitioning methods, collect/sort trade-offs, skew handling). • Familiarity with UNIX/Linux basics and shell scripting for orchestration and file handling. • Experience with job scheduling/orchestration tools (e.g., Control M, Autosys) and CI/CD practices. • Knowledge of common warehousing patterns (incremental loads, slowly changing dimensions, surrogate keys, effective dating). • Experience with version control (Git) and structured promotion/release processes across environments (dev/test/prod). • Exposure to data governance practices (metadata, lineage, naming standards) and secure handling of sensitive data. Education • Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.
Compétences linguistiques
- English
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