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Lead Data Architect – Azure Databricks & Advanced AnalyticsRole OverviewWe are seeking an experienced Lead Data Architect with deep expertise in Azure Databricks and advanced analytics to design and deliver scalable, cloud-native data solutions. This role requires strong hands-on technical skills combined with architectural leadership to drive end-to-end analytics platforms aligned with business objectives.The ideal candidate will bring extensive experience in big data technologies, data engineering, and Azure cloud services, with a strong focus on Databricks, SQL, and modern data lakehouse architectures.Key ResponsibilitiesLead the architecture, design, and implementation of advanced analytics solutions using Azure Databricks and Microsoft FabricCollaborate closely with business stakeholders and cross-functional IT teams to gather requirements and translate them into effective data solutionsOwn end-to-end delivery of data platforms, ensuring alignment with business needs, architectural standards, and best practicesDesign and develop scalable data pipelines and ETL/ELT processes using Azure Databricks, PySpark, and related toolsIntegrate Azure Databricks with other Azure services, including Azure Data Lake, Azure Synapse, Azure Data Factory, and on-premise systemsProvide technical leadership and mentorship to data engineering teams, fostering continuous learning and innovationEnsure comprehensive documentation of data architectures, pipelines, and data flowsEnforce best practices for code quality, data security, governance, and scalabilityStay current with evolving Databricks and Azure technologies to drive continuous improvement and innovationEssential Technical SkillsStrong hands-on experience with Azure Databricks, including cluster management, notebook development, and Delta LakeProficiency in big data technologies such as Spark, Hadoop, and data processing frameworks like PySparkDeep understanding of Azure services including Azure Data Lake Storage (ADLS Gen2), Azure Synapse, and Azure Data FactoryExperience designing and implementing ETL/ELT pipelines, data lakes, and data warehousesAdvanced SQL skills and familiarity with NoSQL databasesExperience with CI/CD pipelines and version control systems such as GitStrong knowledge of cloud security and governance best practicesSoft SkillsExcellent communication skills with the ability to explain complex technical concepts to non-technical stakeholdersStrong problem-solving mindset with a proactive approach to identifying and resolving issuesProven leadership and mentoring skills, with experience leading and guiding data engineering teamsNice to Have SkillsExperience with Power BI for dashboarding and reportingExposure to Microsoft Fabric for analytics and integration workloadsKnowledge of Spark Streaming for real-time data processingFamiliarity with Azure Resource Manager (ARM) templates and Infrastructure as Code (IaC) practicesExperience Requirements12+ years of demonstrated experience in developing data ingestion and transformation pipelines using Databricks, Azure Synapse notebooks, and Azure Data FactoryStrong hands-on experience with Delta Tables, Delta Lake, and Azure Data Lake Storage Gen2Proven expertise using Auto Loader and Delta Live Tables for efficient data ingestion and transformationExperience building and optimizing query layers using Databricks SQLDemonstrated experience integrating Databricks with Azure Synapse, ADLS Gen2, and Power BI for end-to-end analytics solutionsPrior experience developing, optimizing, and deploying Power BI reportsSolid understanding of modern CI/CD practices, particularly for Databricks and cloud-native architectures
