Azure Data Engineer (ID: 4098)

Job title: Azure Data Engineer (ID: 4098)

As an Azure Data Engineer, you will

• Design, develop, and maintain scalable data pipelines using Microsoft Azure data services.
• Develop data processing and transformation solutions using Python.
• Build, configure, and manage data workflows using Azure Data Factory (ADF).
• Develop and optimize data processing solutions using Azure Databricks and Apache Spark.
• Integrate data from multiple sources using APIs and other data integration techniques.
• Work with Azure Databricks and Azure data services to process, transform, and prepare data for analytics and reporting.
• Implement data ingestion, transformation, and loading processes to support business requirements.
• Monitor data pipelines, troubleshoot failures, and resolve data processing issues.
• Optimize pipeline performance, reliability, and scalability.
• Collaborate with cross-functional teams to understand data requirements and deliver effective technical solutions.
• Follow coding standards, version control practices, testing procedures, and Agile ways of working.
• Maintain technical documentation and support data platform improvements.

What You Bring to the Table

• 4–6 years of professional experience in data engineering, Azure data solutions, or related technical roles.
• Hands-on experience with Microsoft Azure data engineering services.
• Strong programming knowledge in Python for data processing and transformation.
• Experience developing and maintaining data pipelines using Azure Data Factory.
• Practical experience with Azure Databricks and Apache Spark.
• Experience integrating data from external systems using APIs.
• Understanding of data ingestion, transformation, ETL/ELT processes, and data integration concepts.
• Knowledge of data pipeline monitoring, troubleshooting, and performance optimization.
• Familiarity with Agile methodologies and collaborative development practices.
• Strong analytical, problem-solving, and communication skills.

You Should Possess the Ability to :

• Develop reliable and scalable data pipelines using Python, Azure Data Factory, and Azure Databricks.
• Extract, transform, and load data from different sources into target data platforms.
• Build API-based integrations to ingest data from external applications and systems.
• Process and transform large datasets using Databricks and Spark.
• Troubleshoot pipeline failures, data quality issues, and performance bottlenecks.
• Optimize data processing workflows to improve performance and reliability.
• Collaborate with technical teams and business stakeholders to translate requirements into data engineering solutions.
• Follow established development standards and participate in Agile development activities.
• Document data pipelines, integration processes, and technical solutions.

What We Bring to the Table

• An opportunity to work on Azure-based data engineering projects.
• Exposure to Python development, cloud data integration, and large-scale data processing.
• Opportunities to contribute to data pipeline development and optimization.
• Collaboration with technical teams in an Agile working environment.