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PwC brand and Pune metro increase competition, but specialized certifications reduce applicant density.
Data engineering skills transfer across industries, but mandatory Azure/Databricks certifications increase domain specificity.
Explicit 8-12 years plus mandatory Databricks and Azure certifications create stringent shortlisting filters.
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Design and develop robust data infrastructure and pipelines for efficient data processing and analysis using Azure and Databricks technologies.
Develop, implement, and troubleshoot complex PySpark scripts and SQL stored procedures to enable actionable data insights for clients.
Lead data engineering efforts integrating data factory, Azure Fabric, Synapse, and related cloud-based analytics services, ensuring delivery for client business growth.
8-12 years total experience with minimum 5 years relevant experience at Architect/Managerial level in data engineering.
Mandatory skills: Azure Databricks, PySpark, Data Factory, Azure Fabric; must have Databricks Certified Data Engineer Associate/Professional and DP600 or DP700 Azure certifications.
Proficient in Python scripting, SQL (complex stored procedures), Azure DevOps/GitHub source control, and build/release pipelines.
Education: B.Tech / M.Tech / M.E / MCA / B.E in relevant field.
Experienced in architecting and managing enterprise-scale data analytics solutions on Microsoft Azure platforms.
Strong hands-on capability in developing scalable ETL pipelines with advanced PySpark and Azure toolsets in cloud environments.
Skilled in troubleshooting, debugging, and optimizing data workflows and integrations, suited for advisory roles requiring client-facing technical leadership.