Job Description:
Senior ETL Developer with extensive experience in IBM DataStage, IBM Cloud Pak for Data (CP4D), and Teradata 20. The resource will support enterprise data modernization efforts, including migration of legacy workloads to CP4D, development of robust ETL pipelines, and technical leadership for data quality, governance, and integration initiatives. This role requires strong analytical capabilities, advanced ETL engineering skills, and the ability to work effectively across complex enterprise environments.
Key Responsibilities
- Design, build, enhance, and optimize ETL pipelines using IBM DataStage (parallel/server jobs, performance tuning, job sequencing).
- Support the migration of DataStage workloads from onpremise environments to IBM Cloud Pak for Data (CP4D), including refactoring, modernization, testing, and validation.
- Develop and optimize complex SQL and BTEQ scripts for Teradata 20, supporting large-scale data integrations and analytics workloads.
- Create automation scripts using Python, Shell scripting, and XML for ETL workflows and data processing.
- Apply Master Data Management (MDM) and data governance principles to ensure consistency, quality, and reliability across systems.
- Work collaboratively with MDHHS data architects, DBAs, analysts, business owners, and technical teams to align deliverables with program objectives.
- Conduct troubleshooting, rootcause analysis, and remediation activities for ETL pipeline issues.
- Support Agile delivery, including sprint participation, documentation, testing, and continuous improvement activities.
Required Skills
1+ years of hands-on experience with IBM Cloud Pak for Data (CP4D).
3+ years of strong experience with Teradata 20, including SQL/BTEQ, performance optimization, and working with large enterprise datasets.
5+ of Unix/Linux scripting and system operations
3 + years of Advanced SQL for analysis and ETL support
Preferred Skills
Public health, Health Industry, or State Government experience
Required Education
Bachelor s degree in computer science, Information Systems, Data Analytics, or related field.
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