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Tier-1 employer and Bengaluru metro increase competition, but senior, niche Azure Databricks expertise limits applicant pool.
Core Azure Databricks and PySpark skills transfer across industries, though aerospace domain experience is a plus.
Mandatory 12+ years and specific Azure Databricks/PySpark Lakehouse expertise create strict shortlisting filters.
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Architect and implement scalable cloud-based ETL/ELT solutions using Azure Data Platform including Azure Databricks, PySpark, Data Factory, and ADLS.
Lead and mentor distributed data engineering teams, providing technical guidance, delivery oversight, and architectural governance.
Drive stakeholder management, cloud modernization, CI/CD pipeline implementation, and enterprise data governance on Azure-based Lakehouse platforms.
12+ years in Data Engineering, ETL Development, Data Warehousing, or Enterprise Data Architecture or 8+ years with advanced degree.
Strong hands-on expertise in PySpark and Azure Databricks with enterprise-scale distributed data processing experience.
Proven experience architecting Azure cloud ETL solutions using Azure Databricks, Data Factory, ADLS, Synapse, and related Azure services.
Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or related discipline.
Experienced senior individual contributor with strong analytical, problem-solving, and architectural governance skills.
Proficient in designing and implementing Medallion Architecture Lakehouse solutions and YAML-driven ETL frameworks with CI/CD and infrastructure automation.
Skilled at leading cross-functional and global teams in hybrid work environments, managing stakeholder relationships and driving cloud modernization initiatives.