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KPMG India
Associate Consultant - Data Engineer(Python/Pyspark)
KPMG India
Bengaluru•On-site•1-3 Yrs•Jul 8
Job description
Overview
We are seeking a highly skilled Data Engineer with expertise in Python, PySpark, SQL, Azure, and Microsoft Fabric.
Responsibilities
- Collaborate with cross-functional teams to design, develop, and implement scalable data solutions using Python, PySpark, SQL, and Azure services.
- Design, develop, and maintain robust ETL/ELT pipelines for efficient data ingestion, transformation, and integration.
- Leverage Azure Data Factory, Databricks, Microsoft Fabric to build and maintain modern data architectures such as medallion architecture.
- Work closely with Power BI developers and data analysts to enable seamless data integration for reporting and analytics.
- Participate in all phases of the Software Development Lifecycle (SDLC) including requirement gathering, development, testing, and deployment.
- Write efficient, scalable, and optimized code to handle large volumes of structured and unstructured data.
- Ensure data quality, consistency, and reliability across data pipelines and storage systems.
- Collaborate with data scientists, analysts, and product teams to solve business and technical challenges.
- Conduct code reviews and provide constructive feedback to team members.
- Troubleshoot, debug, and resolve data pipeline and performance issues.
- Stay up to date with industry trends and best practices in data engineering and cloud technologies.
Qualifications
- Strong experience in data engineering using Python, PySpark, and SQL.
- Proven expertise in designing and implementing ETL/ELT pipelines for data ingestion, transformation, and integration.
- Solid understanding of relational databases with proficiency in SQL, including creating views and stored procedures.
- Hands-on experience with Azure services such as Azure Data Factory, Azure Databricks, and Azure Synapse Analytics.
- Familiarity with Microsoft Fabric for unified data integration, processing, and reporting.
- Strong experience working with large-scale datasets and distributed computing frameworks like Spark.
- Familiarity with version control systems such as Git.
- Understanding of software development best practices and agile methodologies.
- Strong problem-solving and analytical skills.
- Excellent communication and collaboration skills.
- Good to have knowledge of GenAI concepts including RAG architecture, AI agents, SKILL.md workflows, and AI orchestration frameworks.
- Collaborate with cross-functional teams to design, develop, and implement scalable data solutions using Python, PySpark, SQL, and Azure services.
- Design, develop, and maintain robust ETL/ELT pipelines for efficient data ingestion, transformation, and integration.
- Leverage Azure Data Factory, Databricks, Microsoft Fabric to build and maintain modern data architectures such as medallion architecture.
- Work closely with Power BI developers and data analysts to enable seamless data integration for reporting and analytics.
- Participate in all phases of the Software Development Lifecycle (SDLC) including requirement gathering, development, testing, and deployment.
- Write efficient, scalable, and optimized code to handle large volumes of structured and unstructured data.
- Ensure data quality, consistency, and reliability across data pipelines and storage systems.
- Collaborate with data scientists, analysts, and product teams to solve business and technical challenges.
- Conduct code reviews and provide constructive feedback to team members.
- Troubleshoot, debug, and resolve data pipeline and performance issues.
- Stay up to date with industry trends and best practices in data engineering and cloud technologies.