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Job Description
Structured overview of role & requirementsAbout This Role
Develop and maintain enterprise data products and scalable data pipelines that support reporting, analytics, and GenAI use cases across multiple enterprise domains like Supply Chain, Quality, Finance, and Product Lifecycle.
Apply Data-as-a-Product principles to create reusable, governed data assets with proper metadata, lineage, and quality controls enabling self-service consumption.
Collaborate with cross-functional teams including Product Managers, Data Engineers, Data Scientists to deliver AI-ready, well-structured, and optimized data products for analytics and machine learning applications.
Minimum Requirements
Experience developing and supporting data integration, ETL/ELT processes, data pipelines, and transformations on modern data and cloud platforms.
Working knowledge of data modeling, SQL, data quality practices, metadata management, and data governance at enterprise scale.
Bachelor's degree in Computer Science, Information Technology, Engineering, Data Analytics, or equivalent practical experience.
Work Experience Required: Relevant practical experience preferred, but not explicitly quantified in the JD.
Ideal Candidate Profile
Experienced in Data-as-a-Product operating models with skills in data catalogs, lineage, and certified data products.
Familiar with Agile methodologies and collaborating effectively with cross-functional teams including product management and analytics.
Exposure to AI/ML or GenAI initiatives, particularly in preparing AI-ready datasets and semantic models to support intelligent business solutions.