DataStage EngineerLocation: Orlando, FL | Onsite (5-Days) | Type: Contract |
Build robust, high-performance ETL solutions that transform complex data into trusted business insights.
Capco is seeking a DataStage Engineer with strong IBM InfoSphere DataStage expertise to design, build, and support enterprise-grade ETL solutions. In this role, you will develop reliable file-to-table data transformation pipelines that ingest inbound file feeds and load curated SQL Server tables with a strong focus on performance, auditability, operational resilience, and data quality.
Working alongside business analysts, data modelers, QA engineers, and production support teams, you will deliver scalable data integration solutions that enable accurate and timely business reporting.
What You'll Do
Design, develop, and maintain IBM DataStage ETL jobs to ingest file feeds (CSV, fixed-width, and delimited files) into SQL Server using scalable, supportable ETL patterns.
Build end-to-end ETL pipelines including staging, transformation, validation, reconciliation, auditing, and publishing to downstream schemas while ensuring robust logging and restart capabilities.
Develop and optimize SQL Server stored procedures, T-SQL queries, and ETL processes to meet performance and runtime SLAs.
Monitor, troubleshoot, and resolve ETL failures through root-cause analysis while maintaining operational documentation, runbooks, and deployment artifacts.
Collaborate with cross-functional teams to translate business requirements into reliable, well-documented data integration solutions and participate in code reviews, testing, and release activities.
What We're Looking For
Hands-on experience developing IBM InfoSphere DataStage ETL solutions, including data mapping, transformation logic, and file-based data ingestion.
Experience with Master Data Management (MDM), data analysis, and data governance principles, with the ability to support trusted, high-quality enterprise data.
Strong SQL Server expertise with advanced T-SQL including joins, CTEs, window functions, temporary tables, indexing fundamentals, and query optimization.
Experience designing operationally resilient ETL solutions with parameter-driven design, logging, error handling, auditability, reconciliation, and restart strategies.
Strong understanding of data quality controls including validation, duplicate detection, referential integrity checks, and exception management.
Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.
Bonus Points For
Experience tuning DataStage Parallel Jobs, including partitioning strategies, skew handling, sort optimization, and performance tuning.
Familiarity with UNIX/Linux environments, shell scripting, and enterprise scheduling tools such as Control-M or AutoSys.
Experience with Git, CI/CD pipelines, structured release management, and multi-environment deployments.
Knowledge of data warehousing concepts including incremental loading, slowly changing dimensions, surrogate keys, and effective dating.
Exposure to metadata management, data lineage, governance practices, and secure handling of sensitive information.