Key responsibilities

* Design, implement, and optimize end-to-end ETL pipelines in Microsoft Fabric,
from ingestion through multi-stage transformations to data loading and
delivery.
* Build pipelines and notebooks using Python and PySpark; implement data
validation, error handling, and quality controls.
* Collaborate with business analysts and stakeholders to translate requirements
and accounting logic into transformation rules and data solutions.
* Work with data architects to design schemas and data models (star/snowflake)
and, where needed, OLAP cubes aligned to application requirements.
* Ensure efficient, accurate processing from source systems into Fabric’s data
layers; optimize performance and scalability (partitioning, indexing,
resource tuning).
* Leverage modern tooling and practices (e.g., Azure DevOps for boards, repos,
CI/CD); uphold consistent development standards across the global team.
* Conduct unit, integration, and end-to-end testing; troubleshoot and
continuously improve ETL processes.
* Maintain comprehensive, up-to-date documentation (processes, sources,



data
flows, models) accessible to stakeholders; ensure compliance with policies
and standards.

Required skills and experience

* High proficiency with Microsoft Fabric ETL; experience with related tools
such as Azure Data Factory.
* Strong SQL for extraction, transformation, and querying; hands-on with SQL
Server, Azure SQL Database, and Synapse Analytics.
* Data engineering fundamentals: data modeling and schema design
(star/snowflake), transformation, and optimization for warehousing/analytics;
experience with OLAP where applicable.
* Proficiency in Python and PySpark for ETL development within Fabric notebooks
and pipelines.
* Experience loading and optimizing data at scale in Fabric and prior exposure
to Azure Synapse and Azure Data Lake.
* Familiarity with Azure DevOps workflows (work tracking, version control,
pipelines) and up-to-date development practices.
* Rigorous testing approach (un

📌 Manager- Data Engineer (Bengaluru)
🏢 KPMG India
📍 Bengaluru