Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Mid-senior data role, metro location, and broad Azure/Databricks skillset drive high competition.
Core SQL/Python/Spark data engineering skills are highly transferable across industries despite Azure emphasis.
Explicit 6–8+ years requirement plus mandatory Azure, Databricks and Spark skills implies high strictness.
Design and develop scalable, real-time data pipelines and ETL/ELT workflows using Azure services to power autonomous AI systems.
Ensure data quality, security, governance, and compliance while optimizing performance and cost efficiency of data processing.
Collaborate with cross-functional teams to support analytics, reporting, machine learning initiatives, and implement CI/CD pipelines.
6–8+ years of experience in Data Engineering.
Minimum 3+ years of hands-on experience with Microsoft Azure data services including Azure Data Factory, Azure Databricks, Azure SQL Database, and related technologies.
Strong proficiency in SQL and Python; experience with building enterprise-scale ETL/ELT solutions and strong understanding of data modeling principles.
Work Experience Required: 6–8+ years as specified. Notice period: Not explicitly mentioned in the JD.
Experienced in architecting and optimizing high-performance data infrastructure for complex enterprise and autonomous AI applications.
Deep expertise in Azure cloud data technologies with ability to build secure, compliant, and efficient data pipelines at scale.
Proven ability to develop reusable frameworks and standards while working collaboratively in cross-functional, innovative environments.