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Metro location and popular Data Engineer title increase competition, offset by niche Microsoft Fabric specialization.
Core data engineering skills are transferable, but Microsoft Fabric and lakehouse specifics reduce cross-industry fit somewhat.
Explicit 7–10 years requirement plus specific Microsoft Fabric, lakehouse, and DevOps skills increase filtering strictness.
Design, build, and maintain scalable enterprise data lakehouse following medallion architecture using Microsoft Fabric.
Develop, deploy, and troubleshoot reliable distributed data pipelines integrating structured and unstructured data for analytics and AI-driven insights.
Implement data quality frameworks and data governance to ensure secure, compliant, and AI/ML-ready data models supporting enterprise reporting and semantic modeling.
7-10 years of work experience in data engineering.
Hands-on expertise in data warehouses, lakehouse platforms, ETL/ELT pipelines, and Microsoft Fabric or similar.
Must work in shifts: 1pm to 10pm shift timing.
Strong technical skills in data modeling, medallion architecture, data governance, and DevOps practices in data engineering context.
Experienced in building enterprise-scale data platforms that support analytics, reporting, and AI/ML use cases.
Proficient in implementing data quality frameworks and governance ensuring compliance and security in data management.
Capable of leading cross-functional teams and communicating complex data engineering solutions to technical and non-technical stakeholders.