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Job Title: Data Engineer (Azure Databricks) Experience: 5+ Years Location: [Mention Location] Employment Type: Full-Time Job Summary We are looking for an experienced Data Engineer with strong expertise in Azure Databricks and SQL to design, build, and optimize scalable data pipelines. The ideal candidate will have hands-on experience in developing ETL workflows, handling structured and unstructured data, and building efficient data models to support analytical and reporting needs. Key Responsibilities Design and implement robust data pipelines (ETL/ELT) using Azure Databricks. Extract, transform, clean, and enrich data from multiple structured and unstructured data sources. Develop scalable data models to support business intelligence and analytics requirements. Handle unstructured textual data (logs, JSON, text files, etc.) alongside structured datasets. Optimize Spark jobs, queries, and pipelines for performance and cost efficiency. Monitor data workflows and troubleshoot data processing issues. Collaborate with data architects, analysts, and business stakeholders to understand requirements. Ensure data quality, integrity, and governance standards are maintained. Implement performance tuning strategies for SQL queries and Spark workloads. Required Technical Skills Strong hands-on experience with Azure Databricks Experience with PySpark / Spark SQL Strong proficiency in SQL Experience with Azure Data Lake (ADLS Gen2) Experience building end-to-end ETL pipelines Knowledge of Delta Lake Experience in data modeling (Star schema, Fact/Dimension design) Experience handling unstructured data formats (JSON, XML, logs, text) Good to Have Experience with Azure Data Factory (ADF) CI/CD implementation in Azure DevOps Experience with streaming data (Kafka / Structured Streaming) Understanding of Lakehouse architecture Exposure to Power BI or other BI tools Educational Qualification Bachelor's degree in Computer Science, Engineering, or related field Skills: azure,data bricks,sql Job Title: Data Engineer (Azure Databricks) Experience: 5+ Years Location: [Mention Location] Employment Type: Full-Time Job Summary We are looking for an experienced Data Engineer with strong expertise in Azure Databricks and SQL to design, build, and optimize scalable data pipelines. The ideal candidate will have hands-on experience in developing ETL workflows, handling structured and unstructured data, and building efficient data models to support analytical and reporting needs. Key Responsibilities Design and implement robust data pipelines (ETL/ELT) using Azure Databricks. Extract, transform, clean, and enrich data from multiple structured and unstructured data sources. Develop scalable data models to support business intelligence and analytics requirements. Handle unstructured textual data (logs, JSON, text files, etc.) alongside structured datasets. Optimize Spark jobs, queries, and pipelines for performance and cost efficiency. Monitor data workflows and troubleshoot data processing issues. Collaborate with data architects, analysts, and business stakeholders to understand requirements. Ensure data quality, integrity, and governance standards are maintained. Implement performance tuning strategies for SQL queries and Spark workloads. Required Technical Skills Strong hands-on experience with Azure Databricks Experience with PySpark / Spark SQL Strong proficiency in SQL Experience with Azure Data Lake (ADLS Gen2) Experience building end-to-end ETL pipelines Knowledge of Delta Lake Experience in data modeling (Star schema, Fact/Dimension design) Experience handling unstructured data formats (JSON, XML, logs, text) Good to Have Experience with Azure Data Factory (ADF) CI/CD implementation in Azure DevOps Experience with streaming data (Kafka / Structured Streaming) Understanding of Lakehouse architecture Exposure to Power BI or other BI tools Educational Qualification Bachelor's degree in Computer Science, Engineering, or related field Skills: azure,data bricks,sql
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