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Job Description
Structured overview of role & requirementsAbout This Role
Develop and maintain enterprise data products by building scalable, reliable data pipelines, transformations, and curated datasets for multiple domains including Supply Chain, Finance, and Quality.
Implement Data-as-a-Product principles to create reusable, discoverable, governed data assets with metadata, lineage, and quality controls enabling self-service and consistent outcomes.
Collaborate with product managers, engineers, and data scientists to deliver AI-ready data products optimized for analytics, machine learning, and Generative AI use cases.
Minimum Requirements
Experience developing and supporting data integration, ETL/ELT processes, data pipelines using modern data platforms and cloud technologies.
Working knowledge of data modeling, SQL, data quality practices, metadata management, and data governance at enterprise scale.
Bachelor's degree in Computer Science, IT, Engineering, Data Analytics, or equivalent practical experience.
Work Experience Required: Not explicitly mentioned in the JD
Ideal Candidate Profile
Experienced in implementing Data-as-a-Product operating models including data catalogs, lineage, and quality frameworks.
Familiarity with AI/ML or Generative AI initiatives involving preparation of AI-ready datasets and semantic or knowledge models.
Skilled at translating business and product requirements into scalable, maintainable, and reusable technical data solutions within Agile, cross-functional teams.