Data Engineer

Key Responsibilities:

• Design and implement scalable and secure data pipelines using Azure Data Factory and Azure Databricks (Spark).
• Utilize Azure cloud services such as Blob Storage, Azure Functions, and API Gateway to build and maintain robust data solutions.
• Develop and maintain code using Python or similar programming languages to support ETL workflows and data transformation processes.
• Collaborate with DevOps teams to set up and manage CI/CD pipelines using Azure DevOps or equivalent toolsets.
• Ensure high code and data quality standards through performance tuning, testing, and documentation.
• Work across the full development lifecycle , from design through deployment and maintenance of distributed systems.
• Leverage knowledge of SQL and NoSQL databases to design effective data models and ensure data reliability.
• Apply Object-Oriented Programming and ETL best practices to develop modular and reusable components.
• Troubleshoot and resolve cloud networking and connectivity issues in collaboration with infrastructure teams.
• Translate complex technical problems into simple and scalable solutions , aligning with architectural best practices.
• Advocate for and implement data governance , monitoring, and quality frameworks to ensure the integrity of business-critical data.

• Proven experience working with Azure Data Engineering services .
• Hands-on experience with Databricks (Spark) and Azure Data Factory .
• Strong programming skills in Python , with a solid grasp of object-oriented programming .
• Experience with Azure DevOps or other CI/CD tools.
• Demonstrated ability to develop and scale high-performance, distributed services .
• Deep understanding of relational and non-relational (NoSQL) databases .
• Familiarity with cloud networking , ETL concepts , and performance tuning.
• Excellent problem-solving abilities and strong understanding of data architecture principles .