Description
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 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 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.
(ref:hirist.tech)
