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Popular early-career data role with Azure specialization increases applicant density.
Core data engineering skills transfer across industries, but Azure/Fabric specialization raises specificity.
Explicit 1+ year requirement plus specific Azure/ETL skills and degree indicates moderate filtering.
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Design, build, and maintain scalable data ingestion and transformation pipelines within Azure Data Factory / Fabric Data Factory and related Azure services.
Integrate source systems into Enterprise Data Lake / Fabric Lakehouse and prepare curated datasets for analytics, reporting, and data science.
Monitor, troubleshoot, optimize, and document data pipelines; follow CI/CD and version control practices; collaborate with onshore teams for quality and consistency.
Bachelor’s degree in Computer Science, Engineering, or related technical discipline, or equivalent practical experience.
1+ years of hands-on experience building data pipelines using Azure Data Factory / Fabric Data Factory or SSIS.
Foundational understanding of data warehousing concepts, data modeling, ETL/ELT patterns, and SQL.
Ability to follow defined architectures, standards, and engineering best practices; clear written and verbal communication skills.
Experienced in working within established architectures and standards on production-quality data solutions in a collaborative onshore-offshore model.
Comfortable supporting analytics, reporting, and data science initiatives through reliable data pipeline management in an Azure ecosystem.
Practitioner of CI/CD, version control, and peer review processes focused on operational stability and continuous improvement.