Job Description

Job Title: Senior ETL Developer IBM DataStage Modernization

Type: Remote

Client Location: Orlando, FL

Description:

We are seeking an experienced Senior ETL Developer with deep expertise in IBM DataStage to design, build, and modernize enterprise-scale ETL pipelines. This role will focus on developing end-to-end DataStage workflows and supporting the modernization of legacy ETL logic by interpreting DataStage XML transition logic and translating it into modern data platforms such as Snowflake or AWS.

The ideal candidate will combine strong ETL engineering skills, advanced SQL expertise, solid UNIX/Linux knowledge, and an understanding of AI-assisted code and metadata translation to support large-scale data transformation initiatives.

Qualifications:

• 6+ years of hands-on experience with IBM DataStage development
• Proven experience building end-to-end ETL workflows, including extraction, transformation, and load processes
• Strong expertise in SQL, including complex joins, subqueries, window functions, and performance tuning
• Solid knowledge of UNIX/Linux fundamentals, including file systems, permissions, and process management
• Hands-on experience with shell scripting (bash/ksh) for job automation and operational support
• Experience working with DataStage job metadata and XML transition logic
• Ability to analyze and translate legacy ETL logic into modern data platforms such as Snowflake, AWS-native services, or data governance tools like Collibra
• Familiarity with AI-assisted development or automation tools used to understand, parse, or accelerate ETL modernization efforts
• Strong understanding of data warehousing concepts, ETL best practices, and data quality frameworks
• Excellent analytical, problem-solving, and communication skills

Responsibilities:

• Design, develop, and maintain IBM DataStage ETL jobs supporting enterprise data platforms
• Build and support end-to-end ETL pipelines, ensuring data accuracy, performance, and scalability
• Analyze DataStage job designs and XML metadata to understand transformation logic and data lineage
• Leverage AI tools and automation techniques to assist in interpreting legacy ETL logic and accelerating modernization
• Translate DataStage transformation logic into Snowflake SQL, AWS-based data pipelines, or (text continues below image)

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