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Mid-level role, metro location, and common Azure/Databricks skills increase applicant competition.
Databricks, PySpark and Azure skills are broadly transferable across industries and roles.
Explicit 3–4 year minimum plus mandatory Databricks, PySpark and Azure/ADF skills enforce strict filtering.
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Develop and manage ETL pipelines using Azure Data Factory and Databricks for cloud-based data processing.
Design, implement, and optimize SQL queries, stored procedures, and Azure data services like Data Lake and Synapse.
Collaborate to integrate data engineering solutions supporting BI tools and analytics platforms.
Bachelor's degree in Computer Science, IT, Electronics and Communications, or equivalent.
3-4 years of professional experience in data engineering with expertise in Azure cloud platform.
At least 3 years of strong hands-on experience with Databricks, PySpark, and SQL.
Experience with Azure Data Lake, Azure Synapse, Azure Data Factory, SQL Data Warehouse, Azure Blob Storage, and creating Data Factory pipelines.
Experienced in building scalable data solutions on Azure ecosystem supporting BI and analytics use cases.
Proficient in both coding (PySpark, SQL) and cloud data engineering operations.
Comfortable working with ETL processes, automation, and data integration across multiple Azure services.