Senior Data Engineer (ID:3385)

• Design, develop, and maintain enterprise-scale data engineering solutions on Microsoft Azure.
• Build and optimize data pipelines using Azure Databricks and Azure Data Factory.
• Develop and maintain PySpark and Python-based data processing frameworks.
• Implement and manage data governance and metadata solutions using Azure Purview, Collibra, and Atlan.
• Perform data modelling to support analytical, reporting, and governance use cases.
• Consume and integrate external and internal APIs to ingest structured and semi-structured data.
• Ensure data quality, lineage, cataloging, and compliance across data platforms., * Architect and implement scalable, secure, and governed data solutions on Azure.
• Build reusable and maintainable PySpark-based data pipelines.
• Translate business and governance requirements into effective data models.
• Integrate multiple data sources using APIs and cloud-native tools.
• Ensure end-to-end data lineage, cataloguing, and compliance.

What We Bring to the Table:

• A digital-first, cloud-focused environment leveraging Microsoft Azure.
• Opportunities to work on complex, large-scale data engineering initiatives.
• A culture that values Agile ways of working and continuous improvement.
• Exposure to advanced data governance platforms and modern data architectures.

• 10+ years of overall experience in Data Engineering and Data Platform development.
• Strong hands-on expertise in Microsoft Azure data services.
• Proven experience with Azure Databricks, PySpark, and Python for large-scale data processing.
• Solid understanding of data concepts, data modelling, and data architecture.
• Practical experience with data governance tools such as Azure Purview, Collibra, and Atlan.
• Hands-on experience in API consumption and data integration.