Azure Data Engineer

Job Description: As an Azure Data Engineer, your role revolves around designing, implementing, and managing data solutions on the Microsoft Azure cloud platform. Here’s a concise job description:

Key Responsibilities:

1. Collaboration and Requirement Understanding:

   • Collaborate with stakeholders to understand data requirements and design scalable, reliable, and secure data architectures on Azure.

2. Data Pipeline Development:

   • Develop and implement data pipelines to ingest, process, and transform data from various sources using Azure Data Factory, Azure Databricks, or other relevant tools.

3. Data Storage Solutions:

   • Design and implement data storage solutions, including Azure SQL Database, Azure Cosmos DB, Azure Data Lake Storage, and Azure Blob Storage.

4. Data Security and Compliance:

   • Implement data security and access controls to protect sensitive information and ensure compliance with regulatory requirements.

5. Performance Optimization:

   • Optimize data processing and storage for performance and cost-efficiency, leveraging Azure services such as Azure Synapse Analytics and Azure Data Lake Analytics.

6. Machine Learning Integration:

   • Build and deploy machine learning models using Azure Machine Learning service for predictive analytics and advanced data insights.

7. Monitoring and Troubleshooting:

   • Monitor data pipelines and data quality, troubleshoot issues, and implement proactive measures to ensure data integrity and reliability.

8. Cross-Functional Collaboration:

   • Collaborate with cross-functional teams to integrate data solutions with applications, BI tools, and other systems.

Skills and Qualifications:

• Strong knowledge of Azure services, including Azure Data Factory, Azure Databricks, Azure SQL Database, Azure Cosmos DB, Azure Data Lake Storage, Azure Blob Storage, Azure Synapse Analytics, and Azure Machine Learning service.
• Proficiency in SQL, Python, or other programming languages for data manipulation and analysis.
• Experience with data engineering tools and techniques, such as ETL processes, data modeling, and data warehousing concepts.
• Understanding of data security principles and regulatory compliance requirements.
• Effective communication skills and the ability to collaborate with stakeholders to understand and address business needs.
• Problem-solving skills and attention to detail for troubleshooting and optimizing data solutions.