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High: Tier-1 brand, metro location, mid-level, and common data-engineer profile increases applicant competition.
High because role demands Azure Databricks, Fabric, PySpark and DP-203 certification, limiting cross-industry portability.
High due to mandatory certifications, specific Azure Databricks/PySpark skills, and explicit 4-8 years requirement.
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Design and build data pipelines, integration, and transformation solutions using Azure Fabric, Data Factory, and Databricks.
Leverage advanced data engineering technologies (Python, PySpark, Azure Analysis Services, Synapse) to enable efficient data processing and actionable insights.
Maintain and troubleshoot data infrastructure including use of source control (GitHub, Azure DevOps) and CI/CD pipelines.
4 to 8 years of total work experience with minimum 3 years relevant data engineering experience.
Mandatory skills: Azure Databricks, PySpark, Azure Data Factory, Azure Fabric, Python scripting, SQL including complex Stored Procedures.
Mandatory certifications: DP-203 (Azure Data Engineer Associate) and Databricks Certified Data Engineer Professional (Architect/Managerial level).
Education: B.Tech / M.Tech / M.E / MCA / B.E in Engineering or Technology field.
Experienced data engineer proficient in Azure ecosystem and big data technologies, focused on delivering scalable data solutions.
Comfortable in managing complex data pipelines and collaborating through source control and automated build/release processes.
Holds advanced certifications indicating mastery of Azure data engineering and Databricks platforms at senior or architect level.