Posted 12 June, 2026
Assistant Manager - SA2 (AI Hub - GDC)
KPMG
BANGALORE,Karnataka,IN,560103
Full Time
Reference: 218_549848_30029769
Roles & responsibilities
Design, develop, and implement data pipelines for scalable solutions using various technologies - Databricks or Microsoft Fabric
Conduct Code reviews and recommend best coding practices
Provide effort estimates to implement solutions, development effort for the proposed solutions
Develop and maintain comprehensive documentation for all proposed solutions. models, including detailed technical specifications, results of testing and evaluation, and datasets used for developing the solutions
Lead Architect and design efforts for Product development and application development for relevant use cases providing guidance and support to team members and clients
Implement best practices of Data Engineering and Architectural solution design, development, Testing and documentation
Participate in team meetings, brainstorming sessions, and project planning activities
Stay up-to-date with the latest advancements in Data Engineering area, to drive innovation and maintain a competitive edge
Stay hands-on with the design, development and validation of systems and models deployed
Collaborate with audit professionals to understand business, regulatory and risk requirements and key alignment considerations for Audit
Drive efforts in the Data Engineering and Architecture practice area
Mandatory technical & functional skills
Databricks/Fabric/Spark Notebooks
SQL/NoSQL databases, Redis,
Full-Stack Development - React, Angular
Data Management: Design, implement, and manage AI-driven data solutions on the Microsoft Azure cloud platform, ensuring scalability and performance.
Data Integration: Develop and maintain data pipelines for AI applications, ensuring efficient data extraction, transformation, and loading (ETL) processes using Azure Data Factory.
Big Data Processing: Utilize big data technologies such as Azure Databricks and Apache Spark to handle, analyze, and process large datasets for machine learning and AI applications.
machine learning frameworks -TensorFlow, PyTorch
Backend frameworks - FastAPI, Django
Preferred technical & functional skills
Experience working with frameworks LangChain/LlamaIndex /LlamaPrase/LlamaCloud/Semantic Kernel etc.
Develop real-time data ingestion and stream-analytic solutions leveraging technologies such as Kafka, Apache Spark (SQL, Scala, Java), Python and Hadoop Platform and any Cloud Data Platform.
Certifications: Relevant certifications such as Microsoft Certified: AI 102, DP 700, DP 900 or AWS certiications
Key behavioral attributes/requirements
Strong analytical, problem-solving, and critical-thinking skills
Excellent collaboration skills, with the ability to work effectively in a team-oriented environment
Excellent written and verbal communication skills, with the ability to present complex technical concepts to non-technical audiences
Willingness to learn new technologies and work on them
#KGS
#LI-SS1
This role is for you if you have the below
Educational qualifications
Minimum qualification required: BTech in Computer Science/ MTech/ MCA - Fulltime education.
Work experience
6 to 8 years of experience in design, develop data centric applications using various tools and technologies eg: Databases,reporting,ETL/ELT,NoSQL etc.
4+ years of experience in designing, architecting solutions using Microsoft Data technologies like ADF/SYNAPSE
Relevant Data Professional certifications - AWS, GCP or Azure
Roles & responsibilities
Design, develop, and implement data pipelines for scalable solutions using various technologies - Databricks or Microsoft Fabric
Conduct Code reviews and recommend best coding practices
Provide effort estimates to implement solutions, development effort for the proposed solutions
Develop and maintain comprehensive documentation for all proposed solutions. models, including detailed technical specifications, results of testing and evaluation, and datasets used for developing the solutions
Lead Architect and design efforts for Product development and application development for relevant use cases providing guidance and support to team members and clients
Implement best practices of Data Engineering and Architectural solution design, development, Testing and documentation
Participate in team meetings, brainstorming sessions, and project planning activities
Stay up-to-date with the latest advancements in Data Engineering area, to drive innovation and maintain a competitive edge
Stay hands-on with the design, development and validation of systems and models deployed
Collaborate with audit professionals to understand business, regulatory and risk requirements and key alignment considerations for Audit
Drive efforts in the Data Engineering and Architecture practice area
Mandatory technical & functional skills
Databricks/Fabric/Spark Notebooks
SQL/NoSQL databases, Redis,
Full-Stack Development - React, Angular
Data Management: Design, implement, and manage AI-driven data solutions on the Microsoft Azure cloud platform, ensuring scalability and performance.
Data Integration: Develop and maintain data pipelines for AI applications, ensuring efficient data extraction, transformation, and loading (ETL) processes using Azure Data Factory.
Big Data Processing: Utilize big data technologies such as Azure Databricks and Apache Spark to handle, analyze, and process large datasets for machine learning and AI applications.
machine learning frameworks -TensorFlow, PyTorch
Backend frameworks - FastAPI, Django
Preferred technical & functional skills
Experience working with frameworks LangChain/LlamaIndex /LlamaPrase/LlamaCloud/Semantic Kernel etc.
Develop real-time data ingestion and stream-analytic solutions leveraging technologies such as Kafka, Apache Spark (SQL, Scala, Java), Python and Hadoop Platform and any Cloud Data Platform.
Certifications: Relevant certifications such as Microsoft Certified: AI 102, DP 700, DP 900 or AWS certiications
Key behavioral attributes/requirements
Strong analytical, problem-solving, and critical-thinking skills
Excellent collaboration skills, with the ability to work effectively in a team-oriented environment
Excellent written and verbal communication skills, with the ability to present complex technical concepts to non-technical audiences
Willingness to learn new technologies and work on them
#KGS
#LI-SS1
