Job Description

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.

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