Azure Data Analytics Architect

Responsibilities:
1. Lead the architecture, design, and implementation of advanced  analytics solutions using Azure  Databricks / Fabric. The ideal candidate will have a deep understanding of big  data technologies,  data engineering, and cloud computing, with a strong focus on Azure  Databricks along with Strong SQL.
2. Work closely with business stakeholders and other IT teams to understand requirements and deliver effective solutions.
3. Oversee the end-to-end implementation of  data solutions, ensuring alignment with business requirements and best practices.
4. Lead the development of  data pipelines and ETL processes using Azure  Databricks , PySpark, and other relevant tools.
5. Integrate Azure  Databricks with other Azure services (e.g., Azure  Data Lake, Azure Synapse, Azure  Data Factory) and on-premise systems.
6. Provide technical leadership and mentorship to the  data engineering team, fostering a culture of continuous learning and improvement.
7. Ensure proper documentation of architecture, processes, and  data flows, while ensuring compliance with security and governance standards.
8. Ensure best practices are followed in terms of code quality,  data security, and scalability.
9. Stay updated with the latest developments in  Databricks and associated technologies to drive innovation.

Essential Skills:
• Strong experience with Azure  Databricks , including cluster management, notebook development, and Delta Lake.
• Proficiency in big  data technologies (e.g., Hadoop, Spark) and  data processing frameworks (e.g., PySpark).
• Deep understanding of Azure services like Azure  Data Lake, Azure Synapse, and Azure  Data Factory.
• Experience with ETL/ELT processes,  data warehousing, and building  data lakes.
• Strong SQL skills and familiarity with NoSQL databases.
• Experience with CI/CD pipelines and version control systems like Git.
• Knowledge of cloud security best practices.

Soft Skills:
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Strong problem-solving skills and a proactive approach to identifying and resolving issues.
- Leadership skills with the ability to manage and mentor a team of  data engineers.

Nice to have Skills:
- Power BI for dashboarding and reporting.
- Microsoft Fabric for  analytics and integration tasks.
- Spark Streaming for processing real-time  data streams.
- Familiarity with Azure Resource Manager (ARM) templates for infrastructure as code (IaC) practices.

Experience:
1. Demonstrated expertise of 8+ years in developing  data ingestion and transformation pipelines using  Databricks /Synapse notebooks and Azure  Data Factory.
2. Solid understanding and hands-on experience with Delta tables, Delta Lake, and Azure  Data Lake Storage Gen2.
3. Experience in efficiently using Auto Loader and Delta Live tables for seamless  data ingestion and transformation.
4. Proficiency in building and optimizing query layers using  Databricks SQL.
5. Demonstrated experience integrating  Databricks with Azure Synapse, ADLS Gen2, and Power BI for end-to-end  analytics solutions.
6. Prior experience in developing, optimizing, and deploying Power BI reports.
7. Familiarity with modern CI/CD practices, especially in the context of  Databricks and cloud-native solutions.