Senior IBM DataStage Consultant-Location-Hybrid @ Orlando, FL-Need Only Locals -No Non-Locals

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Cyber Sphere LLC, is seeking the following. Apply via Dice today! Title - Senior IBM DataStage Consultant Location-Hybrid @ Orlando, FL-Need Only Locals -No Non-Locals Duration Contract Skills Needed: DataStage, ETL Development (Data Mapping and Transformation Implementation), Strong SQL Server w/ advanced T-SQL, File Based Ingestion, etc. Role Description Role summary Software 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 TSQL 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 TSQL (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., ControlM, 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. What Success Looks Like In This Role • File feeds land and load consistently with clear reconciliation results. • Failures are diagnosable from logs and reject outputs without deep forensics. • Jobs meet runtime SLAs through solid DataStage design and SQL tuning. • Mappings and transformations are documented and traceable to requirements. Regards, Sai Srikar Email: