Data Engineer - Azure & Microsoft Fabric

KPMG entities in India are professional services firm(s). These Indian member firms are affiliated with KPMG International Limited. KPMG was established in India in August 1993. Our professionals leverage the global network of firms, and are conversant with local laws, regulations, markets and competition. KPMG has offices across India in Ahmedabad, Bengaluru, Chandigarh, Chennai, Gurugram, Jaipur, Hyderabad, Jaipur, Kochi, Kolkata, Mumbai, Noida, Pune, Vadodara and Vijayawada.

KPMG entities in India offer services to national and international clients in India across sectors. We strive to provide rapid, performance-based, industry-focused and technology-enabled services, which reflect a shared knowledge of global and local industries and our experience of the Indian business environment.

Role Overview:

4-5 yearsof experience in ata Engineering / Azure Data Engineering experienced Data Engineer with strong hands-on expertise across the Microsoft data ecosystem, particularly Microsoft Azure, Microsoft Fabric, Azure Data Factory (ADF), PySpark, SQL, ETL/ELT, Data Warehousing, Medallion Architecture, and Power BI integration.

The ideal candidate will have 4-5 years of relevant data engineering experience, strong Azure Data Factory expertise, and approximately 3 years of hands-on experience with Microsoft Fabric or closely aligned Microsoft modern data platform technologies. The role involves delivering scalable enterprise data solutions for global engagements and KPMG India projects.

Key Responsibilities:

• Design, develop, and maintain scalable data pipelines and integration solutions using Microsoft Fabric and Azure Data Factory.
• Build end-to-end ETL/ELT pipelines to ingest, transform, and integrate structured and semi-structured data from multiple source systems.
• Develop and maintain Microsoft Fabric Lakehouse and Data Warehouse solutions.
• Implement Medallion Architecture using Bronze, Silver, and Gold data layers.
• Develop reusable, production-quality data processing and transformation solutions using PySpark and SQL.
• Use Microsoft Fabric capabilities including Data Pipelines, Lakehouse, Warehouse, Notebooks, and Dataflows.
• Design and maintain analytical data models and optimized datasets for downstream Power BI consumption.
• Implement incremental loading, data validation, data-quality checks, monitoring, logging, and error-handling controls.
• Optimize SQL queries, PySpark transformations, pipelines, and data-processing workloads for performance and scalability.
• Support development and deployment across Development, Test/UAT, and Production environments.
• Apply engineering practices using Git, Azure DevOps, CI/CD, branching, peer review, and controlled release processes.
• Troubleshoot pipeline failures, data discrepancies, transformation issues, and performance problems.
• Collaborate with Data Architects, Business Analysts, Power BI Developers, application teams, and business stakeholders.
• Prepare and maintain technical documentation covering data flows, pipelines, data models, transformation logic, deployment, and operational support.

Required Technical Skills

Microsoft Azure & Azure Data Factory:

• Strong hands-on experience with Microsoft Azure data services and cloud-based data engineering architecture.
• Strong Azure Data Factory experience, including pipeline development, orchestration, monitoring, troubleshooting, and integration runtime concepts.
• Strong understanding of ETL/ELT concepts, data integration patterns, and incremental data-loading approaches.
• Experience handling structured and semi-structured data.

Microsoft Fabric

• Approximately 3 years of hands-on experience with Microsoft Fabric or closely aligned Microsoft modern data platform technologies.
• Hands-on experience with Fabric Lakehouse, Data Warehouse, Data Pipelines, Notebooks, and Dataflows.
• Strong understanding of Medallion Architecture and Bronze, Silver, and Gold data layers.
• Experience developing transformation and data-processing workloads in Fabric.
• Understanding of enterprise-scale data engineering and analytics patterns.

PySpark & SQL:

• Strong programming and data-transformation skills using PySpark.
• Strong proficiency in SQL, including Stored Procedures and Views.
• Ability to build reusable, maintainable, and optimized transformation logic.
• Experience troubleshooting and tuning data transformations and SQL workloads.

Data Warehousing & Data Modeling:

• Strong understanding of Data Warehouse concepts and dimensional data modeling.
• Knowledge of fact and dimension tables, star schemas, relationships, and analytical data models.
• Ability to design reliable and scalable datasets for downstream analytics and reporting.

Power BI Integration:

The role requires a good understanding of Power BI from a data engineering and analytics integration perspective. Deep dashboard or user-interface development is not the primary expectation.

• Understanding of Power BI semantic models, datasets, relationships, measures, and reporting requirements.
• Ability to prepare optimized data structures for Power BI consumption.
• Understanding of how Microsoft Fabric data platforms connect with Power BI reporting solutions.
• Ability to collaborate effectively with Power BI and reporting teams on data requirements.

DevOps, CI/CD & Version Control

• Hands-on experience with Git and working experience with Azure DevOps.
• Experience working with or implementing CI/CD pipelines for data engineering solutions.
• Understanding of deployment and release practices across Development, UAT/Test, and Production.
• Ability to follow coding standards, branching practices, peer-review processes, security requirements, and deployment controls.

Preferred Certifications

• DP-700 - Microsoft Fabric Data Engineer Associate (especially relevant)
• DP-600 - Microsoft Fabric Analytics Engineer Associate
• PL-300 - Microsoft Power BI Data Analyst
• AZ-900 - Microsoft Azure Fundamentals

Equal employment opportunity information

KPMG India has a policy of providing equal opportunity for all applicants and employees regardless of their color, caste, religion, age, sex/gender, national origin, citizenship, sexual orientation, gender identity or expression, disability or other legally protected status. KPMG India values diversity and we request you to submit the details below to support us in our endeavor for diversity. Providing the below information is voluntary and refusal to submit such information will not be prejudicial to you.