Senior Data EngineerSoftware Engineer with strong ETL experience to design, build, and support file-to-table data transformations using IBM InfoSphere DataStage. You'll turn inbound file feeds into reliable, auditable SQL Server table loads with solid performance, clear error handling, and repeatable operations.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.Apply 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.Ability 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.