Back
Known enterprise, mid-senior Azure data engineer role with common skills yields moderate applicant competition.
Core data engineering skills transfer across industries, though Azure Fabric/ADF specialization increases platform dependency.
Explicit 6–10 years and strict Azure/Microsoft Fabric, PySpark, and data platform requirements enforce rigorous screening.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead architecture, design, and optimization of enterprise-scale data pipelines and ETL/ELT solutions using Microsoft Fabric, Azure Data Factory (ADF), and PySpark.
Own operational excellence and platform administration across Azure Portal and Azure data services including monitoring, cost control, reliability, and security.
Provide technical leadership and collaborate with stakeholders to deliver scalable, secure, and compliant data platforms and analytics-ready datasets.
6–10 years of progressive Data Engineering experience with ownership of large-scale data platforms and technical leadership.
Expertise in SQL engineering including complex transformations, query optimization, and performance tuning.
Hands-on experience with Microsoft Fabric, Azure Data Factory (ADF), Python, PySpark, and Azure data services.
Bachelor’s degree in Computer Science, Information Technology, or related field.
Experienced in modern data warehousing architecture, dimensional modeling, and enterprise data governance.
Skilled in establishing engineering standards, reusable design patterns, and operational best practices for cloud data platforms.
Strong ability to lead cross-functional teams and manage stakeholder relationships in complex technical environments.