Back
Popular mid-level data role with common Azure and Python requirements increases competition to medium.
Core data engineering skills are transferable, but Microsoft Fabric specificity moderately limits cross-cloud portability.
Explicit 2–4 year requirement plus mandatory Azure Synapse, Fabric, and Python increases filter strictness to high.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, develop, and maintain enterprise-grade data pipelines and ETL/ELT processes using Microsoft Fabric, Azure Synapse Analytics, and Data Factory Pipelines.
Build and optimize data transformation workflows including Notebooks using Python, PySpark, and SQL to deliver trusted datasets supporting reporting, analytics, and self-service BI.
Monitor pipeline performance, perform data quality assessments, troubleshoot production issues, and collaborate with BI teams and solution architects to create scalable data engineering solutions.
Bachelor's degree in Computer Science, IT, Engineering, Data Science, or related field.
2–4 years of experience in Data Engineering, Analytics Engineering, or Business Intelligence.
Proficiency in SQL, Python, ETL/ELT development using Azure Synapse Analytics, Microsoft Fabric, and Azure Data Factory.
Hands-on experience with Data Pipelines, Notebooks, Data Warehousing, and Dimensional Data Modeling concepts.
Experienced working with cloud-based analytical platforms and modern data architectures, especially Microsoft Azure ecosystem.
Skilled in building automated, reusable data engineering solutions and supporting CI/CD and release management processes.
Capable of technical documentation, mentoring junior members, and participating in solution architecture discussions for scalable data engineering implementations.