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Job Description
Structured overview of role & requirementsAbout This Role
Develop and maintain scalable enterprise data products and pipelines supporting analytics, AI, automation, and GenAI use cases across multiple enterprise domains.
Implement Data-as-a-Product principles to ensure data assets are reusable, discoverable, governed with metadata, lineage, and quality control.
Collaborate cross-functionally with Product Managers, Engineers, and Data Scientists to deliver AI-ready data products optimized for machine learning and analytics.
Minimum Requirements
Experience in developing and supporting data integration, ETL/ELT processes, data pipelines with modern cloud-based data platforms.
Proficient in data modeling, SQL, data quality, metadata management, and enterprise data governance principles.
Bachelor's degree in Computer Science, IT, Engineering, Data Analytics or equivalent practical experience.
Work Experience Required: Relevant experience preferred but not explicitly quantified; exposure can include internships, co-ops, or academic projects.
Ideal Candidate Profile
Experienced in working within Agile, cross-functional teams collaborating with product, engineering, analytics, and business stakeholders.
Familiarity or experience applying Data-as-a-Product operating models including catalogs, lineage, and certified data products.
Knowledge or exposure to AI/ML or GenAI initiatives, especially in preparing AI-ready datasets and semantic models.