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Job Description
Structured overview of role & requirementsAbout This Role
Develop and maintain enterprise data products by building and optimizing data pipelines and transformations supporting multiple business domains like Supply Chain, Finance, and Product Lifecycle.
Apply Data-as-a-Product principles to create governed, reusable, discoverable data assets with metadata, lineage, and quality controls for self-service and consistent outcomes.
Collaborate cross-functionally with Product Managers, Data Scientists, and Engineers to deliver AI-ready, reliable, well-structured data optimized for analytics, ML, and GenAI applications.
Minimum Requirements
Experience developing and supporting data integration, ETL/ELT processes, and data pipelines using modern data platforms and cloud technologies.
Working knowledge of data modeling, SQL, data quality, metadata management, and enterprise data governance.
Bachelor's degree in Computer Science, IT, Engineering, Data Analytics, or equivalent practical experience.
Work Experience Required: Relevant experience preferred but not strictly quantified; experience with Agile and cross-functional teams is expected.
Ideal Candidate Profile
Experienced in Data-as-a-Product operating models involving data catalogs, lineage, and certified data products.
Proficient in translating business and product requirements into scalable, maintainable data solutions with performance optimization.
Familiarity or exposure to AI/ML, GenAI data preparation, semantic models, or intelligent business data structures.
