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Generalist Data Engineer role with broad skills listed and moderate employer brand.
Core data engineering skills transfer across industries, though enterprise domain knowledge is beneficial.
No explicit years but requires enterprise ETL, cloud, data governance and platform experience.
Develop and maintain enterprise-scale data pipelines and data products using modern ETL/ELT processes across multiple business domains (Supply Chain, Quality, Finance, Product Lifecycle).
Apply Data-as-a-Product principles to create 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, optimized data solutions for analytics, machine learning, and GenAI use cases.
Experience developing and supporting data integration, ETL/ELT, and data transformations on modern cloud-based platforms.
Bachelor's degree in Computer Science, Information Technology, Engineering, Data Analytics, or equivalent practical experience.
Working knowledge of data modeling, SQL, data quality, metadata management, and data governance principles at enterprise scale.
Work Experience Required: Not explicitly mentioned in the JD.
Experience operating within a Data-as-a-Product framework including use of data catalogs, lineage, and certified data products.
Experience working in Agile, cross-functional teams with ability to translate business/product requirements into scalable technical solutions.
Exposure to AI/ML or GenAI data initiatives, including preparation of AI-ready datasets and semantic models.