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Lead Data Architect – Azure Databricks & Advanced Analytics Role Overview We 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 Responsibilities Lead the architecture, design, and implementation of advanced analytics solutions using Azure Databricks and Microsoft Fabric Collaborate closely with business stakeholders and cross-functional IT teams to gather requirements and translate them into effective data solutions Own end-to-end delivery of data platforms, ensuring alignment with business needs, architectural standards, and best practices Design and develop scalable data pipelines and ETL/ELT processes using Azure Databricks, PySpark, and related tools Integrate Azure Databricks with other Azure services, including Azure Data Lake, Azure Synapse, Azure Data Factory , and on-premise systems Provide technical leadership and mentorship to data engineering teams, fostering continuous learning and innovation Ensure comprehensive documentation of data architectures, pipelines, and data flows Enforce best practices for code quality, data security, governance, and scalability Stay current with evolving Databricks and Azure technologies to drive continuous improvement and innovation Essential Technical Skills Strong hands-on experience with Azure Databricks , including cluster management, notebook development, and Delta Lake Proficiency in big data technologies such as Spark, Hadoop , and data processing frameworks like PySpark Deep understanding of Azure services including Azure Data Lake Storage (ADLS Gen2), Azure Synapse, and Azure Data Factory Experience designing and implementing ETL/ELT pipelines, data lakes, and data warehouses Advanced SQL skills and familiarity with NoSQL databases Experience with CI/CD pipelines and version control systems such as Git Strong knowledge of cloud security and governance best practices Soft Skills Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders Strong problem-solving mindset with a proactive approach to identifying and resolving issues Proven leadership and mentoring skills, with experience leading and guiding data engineering teams Nice to Have Skills Experience with Power BI for dashboarding and reporting Exposure to Microsoft Fabric for analytics and integration workloads Knowledge of Spark Streaming for real-time data processing Familiarity with Azure Resource Manager (ARM) templates and Infrastructure as Code (IaC) practices Experience Requirements 12+ years of demonstrated experience in developing data ingestion and transformation pipelines using Databricks, Azure Synapse notebooks, and Azure Data Factory Strong hands-on experience with Delta Tables, Delta Lake, and Azure Data Lake Storage Gen2 Proven expertise using Auto Loader and Delta Live Tables for efficient data ingestion and transformation Experience building and optimizing query layers using Databricks SQL Demonstrated experience integrating Databricks with Azure Synapse, ADLS Gen2, and Power BI for end-to-end analytics solutions Prior experience developing, optimizing, and deploying Power BI reports Solid understanding of modern CI/CD practices , particularly for Databricks and cloud-native architectures
