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Generalist Data Engineer role with common skills and unspecified location, attracting moderate competition.
Core data engineering skills are broadly transferable across industries.
Multiple required data engineering skills and governance expectations imply moderate screening despite no years specified.
Develop and maintain enterprise data products including data pipelines, transformations and curated datasets supporting reporting, analytics, automation, and GenAI use cases across multiple business domains.
Apply Data-as-a-Product principles to create reusable, discoverable, and governed data assets with proper metadata, lineage, and quality controls.
Collaborate with Product Managers, Data Engineers, Data Scientists, and Solution Engineers to deliver AI-ready, reliable, well-structured data optimized for analytics and machine learning applications.
Experience developing and supporting data integration, ETL/ELT, data pipelines, and transformations using modern data platforms and cloud technologies.
Working knowledge of data modeling, SQL, data quality practices, metadata management, and enterprise data governance.
Bachelor's degree in Computer Science, Information Technology, Engineering, Data Analytics, or equivalent practical experience.
Work Experience Required: Not explicitly mentioned in the JD.
Proven ability to translate business and product requirements into scalable, maintainable, high performance technical solutions in data engineering.
Experience working in Agile, cross-functional teams collaborating closely with product, engineering, analytics, and business stakeholders.
Familiarity or experience with Data-as-a-Product operating models, AI/ML or GenAI initiatives, and creating AI-ready datasets and semantic models preferred but not mandatory.