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Job Description
Structured overview of role & requirementsAbout This Role
Develop and maintain enterprise data products and pipelines supporting reporting, analytics, automation, and GenAI use cases across multiple business domains.
Apply Data-as-a-Product principles to ensure reusable, governed data assets with metadata, lineage, and quality controls for self-service consumption.
Collaborate with cross-functional teams (Product Managers, Data Scientists, Engineers) to deliver AI-ready, reliable, well-structured data optimized for analytics and machine learning.
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 practices, metadata management, and data governance for enterprise-scale data products.
Bachelor's degree in Computer Science, IT, Engineering, Data Analytics or equivalent experience.
Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Experienced in Agile cross-functional team environments with product, engineering, analytics, and business stakeholders.
Familiar with Data-as-a-Product operating models including data catalogs, lineage, and data quality frameworks.
Has exposure to AI/ML or GenAI initiatives, preparing datasets and data structures for intelligent business solutions.