Providing innovative, comprehensive, and end-to-end information technology and workforce management solutions that empower businesses to achieve digital transformation, enhance operational efficiency, and drive sustainable growth

About Company

Providing innovative, comprehensive, and end-to-end information technology and workforce management solutions that empower businesses to achieve digital transformation, enhance operational efficiency, and drive sustainable growth.

Job Description

We are seeking a highly skilled DataStage Engineer to join our team in designing, developing, and supporting enterprise-grade ETL solutions for mission-critical business applications. This role is focused on building scalable, high-performance data integration pipelines that transform complex inbound data into trusted business insights. The ideal candidate will possess deep expertise in IBM InfoSphere DataStage, SQL Server, ETL development, data transformation, and enterprise data integration, with a strong focus on performance, operational resilience, auditability, and data quality.

Key Responsibilities

• Design, develop, and maintain IBM InfoSphere DataStage ETL jobs to ingest file-based data (CSV, fixed-width, and delimited files) into SQL Server using scalable and reusable ETL frameworks.
• Build end-to-end ETL pipelines including data staging, transformation, validation, reconciliation, auditing, logging, and publishing to downstream systems.
• Develop, optimize, and maintain SQL Server stored procedures, T-SQL queries, and ETL workflows to meet performance, scalability, and runtime SLAs.
• Design parameter-driven ETL solutions with robust logging, exception handling, restartability, and operational monitoring capabilities.
• Monitor, troubleshoot, and resolve ETL failures through root cause analysis while ensuring operational stability and data integrity.
• Collaborate with business analysts, data modelers, QA teams, and production support teams to translate business requirements into reliable and scalable data integration solutions.
• Participate in code reviews, unit testing, system testing, deployment, and production release activities.
• Implement enterprise data quality controls including validation, duplicate detection, reconciliation, referential integrity, and exception management.
• Maintain ETL documentation, deployment artifacts, operational runbooks, and technical design specifications.
• Optimize ETL job performance through efficient DataStage Parallel Job design, SQL tuning, and workload optimization.
• Support enterprise data governance, metadata management, and secure handling of sensitive business data.
• Contribute to continuous improvement initiatives by recommending ETL best practices, reusable components, and performance enhancements.

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical discipline (or equivalent practical experience).
• 5+ years of hands-on experience developing enterprise ETL solutions using IBM InfoSphere DataStage.
• Strong expertise in designing and developing file-based ETL pipelines and data transformation processes.
• Advanced experience with Microsoft SQL Server and T-SQL, including joins, CTEs, window functions, stored procedures, temporary tables, indexing, and query optimization.
• Strong understanding of enterprise ETL architecture, data mapping, transformation logic, and data integration best practices.
• Experience implementing parameter-driven ETL frameworks with logging, auditing, reconciliation, restartability, and error handling.
• Hands-on experience with Master Data Management (MDM), data governance principles, and enterprise data quality practices.
• Strong understanding of data validation, referential integrity, duplicate detection, and exception management.
• Excellent analytical, troubleshooting, and problem-solving skills.
• Strong communication and collaboration skills with the ability to work effectively across cross-functional teams.

Preferred Qualifications

• Experience tuning IBM DataStage Parallel Jobs, including partitioning strategies, skew handling, sort optimization, and overall ETL performance tuning.
• Familiarity with UNIX/Linux operating systems and shell scripting.
• Experience working with enterprise job scheduling tools such as Control-M or AutoSys.
• Knowledge of Git, CI/CD pipelines, structured release management, and multi-environment deployment processes.
• Strong understanding of data warehousing concepts including incremental loading, Slowly Changing Dimensions (SCD), surrogate keys, and effective dating.
• Experience with metadata management, data lineage, and enterprise data governance frameworks.
• Familiarity with secure data handling practices and regulatory compliance requirements.
• Experience working in consulting or client-facing environments.
• Exposure to cloud-based data platforms and modern data integration technologies is a plus.