Back
Metro-based, mid-level Data Engineer with popular title and broad Azure Databricks skills, highly competitive candidate pool.
Azure Databricks and Azure-platform expertise requires specific cloud experience, moderately limiting cross-industry transferability.
Multiple mandatory Azure Data Factory/Databricks/Synapse, Python/Scala, and explicit 5–8 years requirement enforce strict shortlisting.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead design and architecture of large-scale data infrastructure and ETL/ELT pipelines primarily on Azure Databricks and Data Lakehouse.
Optimize data storage and compute costs across Azure Databricks clusters and Data Lake while ensuring pipeline reliability and security.
Mentor global teams including data scientists, analysts, and operations while driving best practices in data governance and troubleshooting production issues.
5–8+ years of experience in data engineering or platform roles.
Expert hands-on experience with Azure Data Factory, Azure Databricks, and Azure Synapse Analytics.
Strong proficiency in SQL, data modelling (OLAP, OLTP, dimensional modelling), and Python/Scala for Spark job development.
Not explicitly mentioned: educational qualifications and notice period.
Experienced in designing and optimizing large-scale Azure data infrastructure with a focus on cost and performance.
Skilled in applying data governance, security, and compliance practices (RBAC, encryption, GDPR) within data pipelines.
Experienced in collaborating and mentoring across global, cross-functional data teams in complex environments.