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Popular Data Engineer role in a metro location with broad skills increases competition.
Core data engineering skills transfer across industries though enterprise domain knowledge is beneficial.
Requires concrete data engineering, cloud and governance experience, so moderate technical filtering applies.
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Develop and maintain enterprise data products including data pipelines and curated datasets to support reporting, analytics, automation, and GenAI use cases across multiple business domains.
Apply Data-as-a-Product principles to create reusable, discoverable, governed data assets with metadata, lineage, and quality controls.
Collaborate with Product Managers, Data Engineers, Data Scientists, and Solution Engineers to deliver AI-ready data products optimized for machine learning and analytics.
Experience developing and supporting data integration, ETL/ELT processes, and data pipelines using modern cloud-based data platforms.
Working knowledge of data modeling, SQL, data quality, metadata management, and data governance for enterprise-scale data products.
Bachelor's degree in Computer Science, IT, Engineering, Data Analytics, or equivalent practical experience.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in Data-as-a-Product operating model including data catalogs, lineage, and certified data products.
Familiarity with AI/ML or GenAI initiatives and preparing AI-ready datasets and semantic models.
Ability to translate business requirements into scalable, maintainable, and performant technical solutions in Agile, cross-functional teams.