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# IBM DataStage Tech Lead

- **Company:** Hexaware Technologies
- **Location:** McLean, VA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Amazon Web Services, Batch Processing, Cloud Computing, Cloud Database, Code Review, Information Engineering, Extract Transform Load (ETL), Data Transformation, Data Systems, Relational Databases, IBM InfoSphere DataStage, Python (Programming Language), Unix Shell, Performance Tuning, Cloud Services, Shell Script, SQL Databases, Systems Integration, Planning Software, Freeform SQL, Snowflake, Software Troubleshooting, Pyspark, Data Management, Data Pipelines
- **Published:** August 26, 2026
- **Apply:** https://www.dice.com/job-detail/caea321a-8606-4957-b332-7e740a586c8d

## About the Role

Strong hands-on experience with IBM DataStage, preferably version 11.x or later.
Proficiency in SQL and relational database concepts.
Strong experience with UNIX/Linux Shell scripting.
Experience designing, developing, and supporting enterprise ETL and batch-processing solutions.
Practical knowledge of Python and PySpark for data engineering and pipeline development.
Experience working with cloud platforms such as AWS.
Experience with cloud data warehouses, particularly Snowflake.
Strong troubleshooting, analytical, and performance-tuning skills.
Experience working in Agile development environments and collaborating with cross-functional teams.

## Description

We are seeking an experienced ETL Developer to design, develop, maintain, and modernize enterprise data integration solutions. The role involves building robust ETL pipelines, upgrading legacy batch processes, integrating with cloud data platforms, and collaborating with cross-functional Agile teams to deliver scalable and high-performing data solutions., Design, develop, test, deploy, and support enterprise ETL applications using IBM DataStage, typically version 11.x or later.
Develop and maintain reliable Extract, Transform, and Load pipelines for enterprise data processing.
Modernize legacy batch processes and migrate workloads to contemporary data platforms and architectures.
Integrate data solutions with cloud technologies, including AWS and Snowflake.
Build scalable and efficient data pipelines using Python and PySpark.
Write, optimize, and troubleshoot complex SQL queries and data transformations.
Develop and maintain UNIX Shell scripts to support ETL workflows and batch processing.
Monitor production jobs, investigate failures, and implement corrective actions to ensure operational stability.
Tune ETL jobs and data pipelines for performance, scalability, and reliability.
Collaborate with product owners, data analysts, developers, testers, and other stakeholders within Agile teams.
Participate in requirements analysis, technical design, code reviews, testing, deployment, and production support activities.
Support integration with legacy technologies and enterprise scheduling platforms.


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