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Tier-1 brand, metro location, mid-level generalist data role with broad Azure/Databricks requirements increases competition.
Technical Azure/Databricks/PySpark skills are transferable, but advisory consulting context raises sensitivity to medium.
Mandatory certifications (DP-203, Databricks) and specific Azure/PySpark skills make filters highly stringent.
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Develop and implement data pipelines and transformation solutions using Azure Data Factory, Databricks, Azure Fabric, and SQL databases.
Leverage Python and PySpark scripting for complex data analysis and troubleshooting within data infrastructure systems.
Manage source control and deployment processes using GITHUB or Azure DevOps, ensuring robust build and release pipelines.
4 to 8 years of total work experience with minimum 3 years in relevant Azure data engineering technologies.
Mandatory certifications: DP-203 (Azure Data Engineer Associate) and Databricks Certified Data Engineer Professional.
Proficient in Azure Data Factory, Azure Databricks (advanced level), Azure Fabric, PySpark, Python scripting and SQL (complex stored procedures).
Educational qualification: Bachelor of Engineering/Technology, M.Tech, M.E, or MCA.
Experienced in enterprise data engineering environments focusing on cloud-based Azure services and big data platforms.
Skilled in advanced data pipeline development and data transformation with a strong troubleshooting and debugging focus.
Familiar with version control and CI/CD pipelines using GITHUB and Azure DevOps for production-grade data solutions.