Senior Databricks Specialist / Data Architect Role - Qatar

Senior Databricks Specialist / Data Architect Role Experience 5+Yrs Location Qatar Arabic Language Mandatory Overview We are looking for a Senior Databricks specialist with extensive experience designing, implementing, and optimizing enterprise-scale data platforms using Microsoft Azure Databricks. The candidate will be responsible for the architecture, development, optimization, governance, integration, and performance of the organization's Databricks data platform and its integration with Dynamics 365 CRM and other enterprise systems. Key Responsibilities ∙ Design and implement enterprise-scale data solutions using Azure Databricks. ∙Define and maintain Databricks data architecture and platform standards • ∙Design data ingestion and integration pipelines from multiple source systems. ∙Develop scalable ETL/ELT pipelines using Databricks and Apache Spark. ∙Design and implement Medallion Architecture (Bronze, Silver, Gold) where appropriate. ∙Work with Delta Lake and optimize Delta tables and data pipelines. ∙ Design data models and transformation processes for analytical and operational reporting. ∙Integrate Databricks with Microsoft Dynamics 365 / Dataverse and other enterprise applications. ∙Develop and optimize batch and near-real-time data processing pipelines. ∙Implement data quality, validation, monitoring, lineage, and governance processes. ∙Optimize Spark jobs, clusters, SQL queries, Delta tables, and data pipelines for performance and cost. ∙Implement appropriate data security and access controls. ∙ Work with Unity Catalog for data governance, access control, cataloging, and lineage. ∙Support Power BI and other analytical/reporting platforms through optimized data models and data services. ∙Troubleshoot complex data engineering and performance issues. ∙Establish development, testing, and production standards for Databricks. ∙Support CI/CD and DevOps practices for Databricks solutions. ∙Conduct technical reviews and mentor data engineers. ∙ Ensure data platform solutions meet security, availability, scalability, and disaster recovery requirements. Mandatory Technical Requirements ∙Minimum 8+ years of experience in data engineering/data architecture. ∙Minimum 4+ years of strong hands-on experience with Azure Databricks. ∙Strong hands-on experience with Apache Spark and PySpark. ∙Strong experience with Delta Lake. ∙ Strong experience designing enterprise data platforms and data pipelines. ∙Strong knowledge of Databricks Medallion Architecture. ∙Strong experience with Unity Catalog, data governance, access control, and data lineage. ∙Strong SQL skills and experience with large-scale data processing. ∙ Strong experience with Azure data services. ∙Experience with Azure Data Factory / Azure Data Lake Storage Gen2. ∙Experience integrating Databricks with APIs, enterprise applications, CRM systems, and other data sources. ∙Experience with data modeling and dimensional modeling. ∙Strong understanding of data quality and data governance. ∙Strong understanding of performance optimization and Databricks cost optimization. ∙Experience with CI/CD, Git, Azure DevOps, and deployment automation. ∙Experience working with large-volume enterprise datasets. ∙ Ability to troubleshoot complex production data issues. Preferred Certifications ∙Databricks Certified Data Engineer Professional ∙Databricks Certified Data Engineer Associate ∙Microsoft Certified: Azure Data Engineer Associate ∙ Other relevant Databricks/Azure certifications Candidate Profile The candidate must be a hands-on senior Databricks specialist with proven experience in production enterprise environments. We are specifically looking for someone who can independently design, develop, troubleshoot, optimize, and govern Databricks solutions, rather than someone whose experience is limited to basic Databricks development. Skills: data,architecture,access,enterprise,data governance,design,other,pipelines,integration,azure

Experience 5+ years in data engineering or data architecture. Minimum 8+ years of experience in data engineering/data architecture. Minimum 4+ years of strong hands-on experience with Azure Databricks. Strong hands-on experience with Apache Spark and PySpark. Strong experience with Delta Lake. Strong experience designing enterprise data platforms and data pipelines. Strong knowledge of Databricks Medallion Architecture. Strong experience with Unity Catalog, data governance, access control, and data lineage. Strong SQL skills and experience with large-scale data processing. Strong experience with Azure data services. Experience with Azure Data Factory / Azure Data Lake Storage Gen2. Experience integrating Databricks with APIs, enterprise applications, CRM systems, and other data sources. Experience with data modeling and dimensional modeling. Strong understanding of data quality and data governance. Strong understanding of performance optimization and Databricks cost optimization. Experience with CI/CD, Git, Azure DevOps, and deployment automation. Experience working with large-volume enterprise datasets. Ability to troubleshoot complex production data issues.

Design and implement enterprise-scale data solutions using Azure Databricks. Define and maintain Databricks data architecture and platform standards. Design data ingestion and integration pipelines from multiple source systems. Develop scalable ETL/ELT pipelines using Databricks and Apache Spark. Design and implement Medallion Architecture (Bronze, Silver, Gold) where appropriate. Work with Delta Lake and optimize Delta tables and data pipelines. Design data models and transformation processes for analytical and operational reporting. Integrate Databricks with Microsoft Dynamics 365 / Dataverse and other enterprise applications. Develop and optimize batch and near-real-time data processing pipelines. Implement data quality, validation, monitoring, lineage, and governance processes. Optimize Spark jobs, clusters, SQL queries, Delta tables, and data pipelines for performance and cost. Implement appropriate data security and access controls. Work with Unity Catalog for data governance, access control, cataloging, and lineage. Support Power BI and other analytical/reporting platforms through optimized data models and data services. Troubleshoot complex data engineering and performance issues. Establish development, testing, and production standards for Databricks. Support CI/CD and DevOps practices for Databricks solutions. Conduct technical reviews and mentor data engineers. Ensure data platform solutions meet security, availability, scalability, and disaster recovery requirements.