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Tier-1 brand and metro location increase competition while senior experience requirement moderately narrows the pool.
Requires Azure-specific data engineering and domain skills, limiting easy cross-industry transferability.
Explicit 8–12 years plus mandatory Azure data engineering skills and certifications make shortlisting strict.
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Lead development and delivery of data and analytics products from requirement gathering through user adoption.
Develop, deploy, and maintain cloud data solutions using Azure services such as Azure Data Lake Storage, Azure Data Factory, and Synapse.
Optimize data transformation workflows, SQL queries, and support data modelling and data warehousing initiatives.
7 to 10 years of professional experience in Data & Analytics roles, preferably within global organizations.
Proficiency in Azure cloud services including Azure Data Lake, Azure Data Factory, and Azure Synapse.
Strong SQL skills and experience with data transformation tools like ADF and Databricks (PySpark/Delta).
Education: Bachelor of Engineering (BE/BTech), Master of Business Administration (MBA), or Master of Computer Applications (MCA).
Experienced in end-to-end data product lifecycle management with a focus on user adoption.
Hands-on expertise in developing scalable cloud data solutions using Azure platforms and tools.
Possesses strong technical skills in data warehousing, modelling, and data transformation with knowledge of Python/PySpark/Scala as a plus.