Back
Mid-level generalist Data Engineer title and 3–5 year range create moderate competition despite Azure/Fabric specialization.
Requires Azure and Microsoft Fabric platform expertise, moderately limiting transferability across varied tech stacks.
Explicit 3–5 years plus mandatory Azure, Fabric, PySpark, SQL, and C# skills increase shortlisting rigidity.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, build, and maintain ETL/ELT data pipelines supporting ingestion, transformation, and BI data delivery.
Implement Medallion architecture (Bronze, Silver, Gold layers) for modular, scalable, and quality-focused data processing.
Collaborate cross-functionally to align data solutions with enterprise architecture, data governance, and business requirements across hybrid cloud and on-prem environments.
3–5 years experience in data engineering or similar technical role.
Strong proficiency in SQL and hands-on experience with ETL/ELT development.
Practical experience with Microsoft Fabric (Lakehouse, Warehouse, Pipelines, Notebooks) and Azure data services including ADF, ADLS, Synapse, Databricks, Azure SQL.
Advanced skills in Python, PySpark, and C# for data processing, pipeline development, and automation.
Experienced in building scalable, governed data solutions in hybrid cloud/on-premises environments using modern architectures and tools.
Skilled in collaborating with diverse stakeholders including BI engineers, data architects, analysts, and compliance teams.
Familiar with CI/CD pipelines, version control, DevOps practices and able to deliver reliable, high-quality data engineering solutions under fast-paced conditions.