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Job Description
Structured overview of role & requirementsAbout This Role
Develop and maintain scalable enterprise data pipelines and curated datasets that support reporting, analytics, automation, and GenAI use cases across multiple business domains.
Implement Data-as-a-Product principles to create reusable, discoverable, and governed data assets with metadata, lineage, and quality controls enabling self-service and consistent outcomes.
Collaborate with cross-functional teams including Product Managers, Data Engineers, and Data Scientists to deliver AI-ready data products optimized for analytics and machine learning applications.
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, 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 Data-as-a-Product operating models with familiarity in data catalogs, lineage, and certified data products.
Ability to translate business and product requirements into scalable, maintainable, and reusable technical solutions.
Proven collaborator in Agile, cross-functional teams working with product, engineering, analytics, and business stakeholders around AI/ML or GenAI initiatives.