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Tier-1 client brand, popular data role, metro location, and broad Azure/Databricks requirements increase competition.
Core Azure Databricks and data engineering skills are widely transferable across industries.
Multiple mandatory Azure/Databricks, PySpark, tenant-migration and architecture skills create stringent technical filters.
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Own end-to-end architecture and design of scalable, secure data engineering platforms on Azure cloud.
Lead Azure tenant migration projects for data workloads, including planning, execution, and validation of migrations across Azure and cross-cloud services.
Govern development of data pipelines using Python and PySpark, optimize data warehouse performance, and mentor senior data engineering teams.
Experience Required: Proven solution architecture or senior data architect role focused on Azure cloud data engineering.
Strong hands-on skills with Azure Databricks, Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, Python, PySpark, SQL, and data warehouse optimization.
Past leadership of Azure-to-Azure or cross-cloud (AWS/GCP) data workload migration projects.
Experience with Git-based version control and CI/CD pipeline design for data engineering workloads.
Experienced in architecting and leading large-scale Azure data platform projects including tenant migrations and cross-cloud integrations.
Technically strong in distributed data processing using PySpark and Python, with deep knowledge of Azure PaaS data services and cloud governance.
Capable of driving governance, best practices, and team mentorship within cross-functional and DevOps-oriented environments.