Azure Data Engineer

Responsibilities

• Design, develop, and maintain scalable data pipelines and data integration solutions on the Microsoft Azure platform.
• Build and optimize ETL/ELT workflows using Azure Data Factory (ADF) and Azure Databricks (ADB).
• Develop robust data processing and transformation solutions using Python and Databricks.
• Design and implement batch and near real-time data ingestion pipelines from multiple enterprise data sources.
• Collaborate with data architects, business analysts, and development teams to translate business requirements into scalable data solutions.
• Develop reusable data engineering frameworks that improve reliability, performance, and maintainability.
• Optimize data pipelines for performance, scalability, cost efficiency, and reliability.
• Ensure data quality, governance, and security across the enterprise data platform.
• Troubleshoot and resolve issues related to data ingestion, transformation, and processing.
• Participate in Agile ceremonies and contribute to continuous improvement initiatives within the engineering team.
• Support deployment, monitoring, and maintenance of Azure-based data solutions.

• 4–6 years of experience in Data Engineering or Cloud Data Platform development.
• Strong hands‑on expertise in Python for data engineering and automation.
• Experience designing and developing data pipelines using Azure Data Factory (ADF).
• Strong experience with Azure Databricks (ADB) for data transformation and processing.
• Good understanding of ETL/ELT concepts, data integration, and data migration techniques.
• Experience working with structured and semi‑structured datasets in enterprise environments.
• Knowledge of Azure data platform services and cloud‑native data architectures.
• Familiarity with SQL and data modeling principles.
• Experience working within Agile development teams and collaborative delivery environments.
• Strong analytical, troubleshooting, and problem‑solving skills.

• Design scalable and efficient Azure‑based data engineering solutions.
• Develop and optimize high‑performance data pipelines using Azure Data Factory and Databricks.
• Build reusable Python components for data ingestion, transformation, and orchestration.
• Collaborate effectively with cross‑functional teams to deliver business‑driven data solutions.
• Analyze data processing challenges and implement robust, maintainable solutions.
• Ensure high standards of data quality, security, and operational excellence.
• Adapt quickly to evolving cloud technologies and enterprise data requirements.
• Deliver solutions within Agile methodologies while maintaining quality and performance standards.

• Opportunity to work on modern Azure cloud data engineering and analytics initiatives.
• Exposure to enterprise‑scale data platforms and cloud‑native architectures.
• Collaborative environment with experienced cloud engineers, architects, and data professionals.
• Challenging projects involving large‑scale data integration, transformation, and modernization.
• Opportunities for continuous learning, technical growth, and Azure cloud specialization.
• A culture that encourages innovation, collaboration, and engineering excellence.

Want to discuss this opportunity in more detail? Feel free to reach out.