Senior Associate 2 GTS - DES at KPMG India
Join our dynamic Audit Data Engineering team at KPMG India as a Senior Associate 2. Utilize your skills in data extraction, transformation, and visualization to drive meaningful insights and help us deliver exceptional audit services.
Role Overview
As part of our Audit Data Engineering team, you will develop proficiency in KPMG's proprietary tools and business rules. You will be responsible for extracting, validating, analyzing, and visualizing data from client ERP systems (On-Premise/Cloud). Your contributions will provide critical insights to audit engagement teams across various business processes.
Core Responsibilities
Development
- Build and configure tools for extracting and transforming data from multiple sources.
- Utilize Azure Cloud technologies for ETL processes, providing technical guidance in debugging issues.
- Design, code, verify, document, and amend moderately complex programs/scripts.
- Implement data ingestion, transformation, and validation processes to ensure data quality and reliability using Azure cloud applications.
- Apply data analysis, design, modeling, and quality assurance techniques based on business processes.
- Participate in design, development, and implementation of modules and their enhancements.
- Handle high-level technical specifications and solution design; build and implement fixes and enhancements.
- Develop operational and engagement team routines using chosen technologies.
- Lead sub-modules for new product releases with the ERP functional and testing teams.
- Build and lead your team, delivering from our team and training professionals in Azure data engineering.
Experience with , TensorFlow, Keras, and AI/ML algorithms (k-NN, Naive Bayes, SVM, Decision Forests) is advantageous.
Execution
- Support clients in remote data extraction with medium to high complexity and data size.
- Assist audit engagement teams by coordinating data extraction with client IT teams and technical leads.
- Interpret results and provide meaningful insights from reports.
- Develop data transformations using Azure Databricks, Azure Data Factory, or Python.
- Debug, optimize, and resolve issues in processing large datasets with limited guidance.
- Ensure data integrity and completion across multiple data layers.
- Maintain accurate project status for self and team members.
- Prepare and review engagement documents with attention to detail.
- Handle and analyze large data volumes using Azure Databricks and Apache Spark, creating workflows and data pipelines.
- Coach Associates on data processing best practices for lower complexity work.
Job Requirements
Technical Skills
- Primary Skills: Azure Data Factory, Azure Data Lake Storage, Azure Databricks, Azure Synapse Analytics, Python or Pyspark, SQL/PLSQL
- 6+ years of IT experience in ETL and Microsoft Azure.
- Experience in building ETL/ELT processes and data ingestion/migration.
- Proficient in writing Python or Pyspark notebooks for data transformation integrating with Azure Data Lake Storage.
- Ability to monitor, troubleshoot, and optimize Databricks notebooks, Azure Data Factory, and Synapse workloads.
- Hands-on experience with Azure Cloud Services.
- Strong knowledge of Python and PySpark, capable of developing and debugging data workflows.
- Familiarity with data concepts like partitioning, optimization, and tuning.
- Experience with General Ledger/Sub-Ledger analysis and audit/internal audit risk assessments.
- Proficiency in database architecture and data modeling.
- Understanding of visualization tools or Power Apps is advantageous.
- Knowledge of KQL (Kusto Query Language), Azure REST APIs.
- A Certified DP203 Data Engineer certification is a plus.
- Experience in SQL queries and database management (Oracle/SQL