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Remote posting, mid-level generalist title, and popular data role increase competition despite niche Azure skills.
Requires specialized data engineering and Azure platform expertise, limiting cross-industry interchangeability.
Explicit 5+ years and mandatory Azure Databricks, PySpark, and data platform requirements make filters stringent.
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Design, develop, and maintain end-to-end data integration and pipeline solutions using Azure Data Factory, Databricks, and Synapse Pipelines to ensure scalable and efficient data processing.
Lead architecture and implementation of Databricks lakehouse solutions with performance optimization of Spark jobs and robust data governance.
Build and manage application and API integrations with Azure Functions, Logic Apps, Service Bus/Event Grid, and Azure API Management to enable seamless, secure data flow across enterprise systems.
5+ years of experience in Data Engineering or Data Platform development.
3+ years of hands-on experience with Azure Databricks and strong skills in Azure Data Factory, ADLS Gen2, and Synapse Analytics.
Proficiency in Python (PySpark), SQL, and Databricks notebooks for developing scalable ETL/ELT workflows.
Experience building application and API integrations using Azure Functions, Logic Apps, Service Bus/Event Grid, and Azure API Management.
Experienced in designing scalable enterprise data platforms leveraging Microsoft Azure ecosystem with a focus on integration and performance optimization.
Skilled in operating within Agile/Scrum environments, managing full SDLC for complex data solutions while providing technical leadership.
Capable of translating complex business requirements into robust, well-documented technical architectures and integration workflows with high uptime and stakeholder satisfaction.