Data Engineer 3

Develop and maintain enterprise data products by building scalable data pipelines and curated datasets supporting analytics, automation, and GenAI use cases across multiple enterprise domains.

Apply Data-as-a-Product principles to produce reusable, governed data assets with metadata, lineage, and quality controls enabling self-service and consistent business outcomes.

Collaborate with cross-functional teams including Product Managers, Data Engineers, Data Scientists, and Solution Engineers to deliver AI-ready data optimized for analytics, machine learning, and GenAI applications.

Experience developing and supporting data integration, ETL/ELT processes, data pipelines, and data transformations using modern data platforms and cloud technologies.

Working knowledge of data modeling, SQL, data quality practices, metadata management, and data governance principles at enterprise scale.

Bachelor's degree in Computer Science, Information Technology, Engineering, Data Analytics, or equivalent practical experience.

Work Experience Required: Not explicitly mentioned in the JD

Experienced in Agile, cross-functional team environments collaborating with product, engineering, analytics, and business stakeholders.

Familiar with Data-as-a-Product operating models including data catalogs, lineage, data quality frameworks, and certified data products.

Exposure to AI/ML or GenAI initiatives, including preparing AI-ready datasets and semantic models for intelligent business solutions.