Azure Data Engineer

Role accountabilities:

• Possess excellent design and coding skills and a zeal for owning the complete SDLC of building applications in a DevOps environment
• You are excited about working with Azure Data Platform
• challenges while building the next wave of software engineering solutions
• Collaborating with and across Agile teams to design, develop, test, implement, and support technical solutions in Microsoft Azure Data Platform
• Leading the craftsmanship, security, availability, resilience, and scalability of your solutions
• Very strong on database concepts, data modelling, stored procedures, complex query writing, performance optimization of SQL queries.
• Strong experience in
• T-SQL, SSIS, SSAS, SSRS
• Azure Data Factory
• Azure Data Lake Store
• Azure Data Lake Analytics (Good to have, not mandatory)
• Azure SQL DB
• Azure SQL DW
• Azure Analysis Services, DAX
• Azure Data Bricks with Python/Scala
• Experience in building end to end solution using Azure data analytics platform.
• Experience in building generic framework solution which can be reused for upcoming similar use cases.
• Experience in building Azure data analytics solutions with DevOps (CI/CD) approach.
• Experience in using TFS, Azure Repos.
• Mentor peers to gain expertise on Azure data platform solutions skills.
• Experience in developing, maintaining, publishing, and supporting dashboards using Power BI.
• Strong experience in publishing dashboards to Power BI service, using Power BI gateways, Power BI Report Server & Power BI Embedded

Qualifications & Experience:

Basic Qualifications:

• Bachelor's in Engineering/Math/Statistics/Econometrics or related discipline
• Should have 3-8 years of experience in MSBI with relevant hands-on experience in Azure Data Platform (must) for a minimum of 3 years.

Required Skills & Experience

• Intermediate-level hands-on experience with Microsoft Fabric:
  Pipelines, Dataflows Gen2, ADLS Gen2, Notebooks, Lakehouse, Warehouse, Delta tables.
• Expertise in SQL (complex transformations, joins across modules, optimization, indexing strategies).
• Strong hands-on experience in PySpark, Delta Lake operations, and scalable distributed processing.
• Ability to build scalable and optimized data pipelines following best engineering practices.
• Experience with performance tuning, query optimization, and pipeline runtime improvement.
• Strong understanding of incremental load vs. full load mechanisms, including change detection, Delta merge operations, surrogate key handling, and data reconciliation.
• Experience working with Fabric notebooks, merging/joining large datasets, and handling incremental vs full loads.
  • Strong communication skills and the ability to understand the business logic behind systems.