Senior-KDNI

Role overview

Senior-KDNI at KPMG

The role involves developing and managing end‑to‑end data pipelines, integrating data from multiple sources, and ensuring reliable data ingestion, transformation and processing using spark.

Responsibilities

• Design, build, and maintain scalable data solutions on Microsoft Azure to support business data needs.
• Implement data security, governance, and privacy controls across Azure data platforms.
• Monitor, troubleshoot, and optimize data workflows to ensure reliability, performance, and cost efficiency.

Required qualifications

• Bachelor’s or higher degree in Computer Science or a related discipline; or equivalent (minimum 3 years work experience).
• At least 3 years of consulting or client service delivery experience on Azure Microsoft data engineering.
• At least 3; years of experience in developing data ingestion, data processing and analytical pipelines for big data, relational databases such as SQL server and data warehouse solutions such as Azure Databricks, Microsoft Fabric Hands-on experience implementing data ingestion, ETL and data processing using Azure services: Fabric, onelake, ADLS, Azure Data Factory, Azure Functions, services in Microsoft Fabric etc.
• Minimum of 3 years of hands-on experience in Azure and Big Data technologies such as Fabric, databricks, Python, SQL, ADLS/Blob, pyspark/SparkSQL.
• Minimum of 3 years of RDBMS experience Experience in using Big Data File Formats and compression techniques.

Employment details

• Location: Pune [Maharashtra] [India]

Additional role details

• Experience working with Developer tools such as Azure DevOps, Visual Studio Team Server, Git, etc An Azure Data Engineer is responsible for designing, building, and maintaining scalable data framework on the Azure data requirements.
• The Azure Data Engineer also implements data security, privacy, and governance controls, monitors and troubleshoots data workflows, and continuously optimizes data storage and processing to achieve high performance and cost efficiency across Azure data platforms
• Develop and manage data pipelines for ingesting, transforming, and integrating data from multiple sources.
• Optimize data storage and processing solutions by leveraging Azure best practices and services.
• Bachelor of Engineering/Mtech