We are seeking a Senior Azure Data Engineer to lead the design, development, and optimization of enterprise-scale data platforms on Microsoft Azure.

The ideal candidate will bring deep expertise in Azure Data Factory, SQL, and Microsoft Fabric, and will play a critical role in defining data architecture standards, best practices, and mentoring junior engineers.

Key Responsibilities :

- Architect and lead the development of scalable, secure, and high-performance data pipelines using Azure Data Factory.

- Design and implement end-to-end data solutions using Microsoft Fabric, including Lakehouse, Data Engineering, and Data Warehouse components.

- Optimize complex SQL queries and data models to ensure performance, reliability, and scalability.

- Define and enforce data architecture standards, best practices, and governance frameworks.

- Lead data ingestion from multiple sources, including on-premises systems, cloud platforms, APIs, and streaming data.

- Monitor, troubleshoot, and optimize data pipelines and overall system performance.

- Collaborate closely with business and technical stakeholders to translate requirements into robust technical solutions.

- Mentor junior data engineers and conduct code and design reviews.

- Ensure security, compliance, and cost optimization across Azure data services.

- Create and maintain architecture diagrams, technical documentation, and design artifacts.

Required Skills & Qualifications :

- 6+ years of experience in Data Engineering.

- Strong hands-on expertise with Microsoft Azure Cloud services.

- Advanced experience with Azure Data Factory.

- Expert-level SQL proficiency, including performance tuning, indexing, and complex transformations.

- Strong hands-on experience with Microsoft Fabric.

- Solid understanding of ETL/ELT patterns, data warehousing concepts, and analytics architectures.

- Proven experience designing and supporting large-scale, high-volume data solutions.

Good to Have :

- Experience with Azure Synapse Analytics.

- Knowledge of Spark / PySpark.

- Experience with Power BI and semantic data models.

- Exposure to CI/CD pipelines using Azure DevOps.

- Familiarity with data governance and metadata management tools.