Manager (AI Hub GTS)

Roles & responsibilities

• Lead the design, development, and implementation of scalable data engineering solutions using platforms such as Databricks and Microsoft Fabric, aligning with enterprise architecture and business goals.
• Own the architectural vision for product and application development, ensuring alignment with organizational strategy and technical standards.
• Drive innovation by evaluating emerging technologies and integrating them into solution roadmaps.
• Establish and enforce coding standards and best practices across teams through structured code reviews and technical mentoring.
• Oversee the estimation process for solution development efforts, ensuring accuracy and alignment with delivery timelines and resource planning.
• Ensure comprehensive documentation of solutions, including technical specifications, testing protocols, and datasets, to support maintainability and audit readiness.
• Provide technical leadership and guidance to cross-functional teams, fostering a culture of excellence and continuous improvement.
• Collaborate with audit professionals and business stakeholders to understand regulatory, risk, and operational requirements, ensuring solutions are compliant and value-driven.
• Facilitate knowledge sharing through team meetings, brainstorming sessions, and technical workshops.
• Champion best practices in data engineering, architecture design, testing, and documentation to ensure high-quality deliverables.
• Stay hands-on with critical aspects of system and model design, development, and validation to ensure robustness and scalability.
• Monitor and optimize performance of deployed systems, proactively identifying areas for improvement.
• Lead initiatives within the Data Engineering and Architecture practice area, contributing to capability building, asset development, and strategic growth.
  

Stay abreast of industry trends and advancements to maintain a competitive edge and drive continuous innovation.
Mandatory technical & functional skills

• Strong understanding of MPP databases and RDBMS fundamentals
• Hands-on experience with Cloud Platforms (SaaS/PaaS) preferably AZURE
• Expertise on cloud databases and Datawarehouse EG: AZURE SQL,SYNAPSE etc.
• Working knowledge with NoSQL databases EG: MongoDB,Cassandra,Redis
• In-Depth knowledge of SPARK ecosystem and APIs
• Exposure into Databricks and pySpark
• Clear understanding of datalakes and data lakehouses
• Decent understanding of Unity catalog, Delta live tables,MLFlow etc.
• Exposure into streaming
• Solid knowledge with building data pipelines using ADF,SYNAPSE,GLUE etc.
• Familiarity with Event Driven designs and messaging using service bus, Event grid
• Exposure into Serverless orchestrators EG: LogicApp,Function App,Airflow etc.
  

Familiarity with CI/CD using Git actions or AZURE devOps

Preferred Technical & Functional Skills

• Backend frameworks - FastAPI, Django
• Machine learning frameworks -TensorFlow, PyTorch
• RestAPI
• Experience working with frameworks LangChain/LlamaIndex /LlamaPrase/LlamaCloud/Semantic Kernel etc.
• Certifications: Relevant certifications such as Microsoft Certified: AI 102, DP 700, DP 900 or AWS certifications
  

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

Responsibilities

Roles & responsibilities

• Lead the design, development, and implementation of scalable data engineering solutions using platforms such as Databricks and Microsoft Fabric, aligning with enterprise architecture and business goals.
• Own the architectural vision for product and application development, ensuring alignment with organizational strategy and technical standards.
• Drive innovation by evaluating emerging technologies and integrating them into solution roadmaps.
• Establish and enforce coding standards and best practices across teams through structured code reviews and technical mentoring.
• Oversee the estimation process for solution development efforts, ensuring accuracy and alignment with delivery timelines and resource planning.
• Ensure comprehensive documentation of solutions, including technical specifications, testing protocols, and datasets, to support maintainability and audit readiness.
• Provide technical leadership and guidance to cross-functional teams, fostering a culture of excellence and continuous improvement.
• Collaborate with audit professionals and business stakeholders to understand regulatory, risk, and operational requirements, ensuring solutions are compliant and value-driven.
• Facilitate knowledge sharing through team meetings, brainstorming sessions, and technical workshops.
• Champion best practices in data engineering, architecture design, testing, and documentation to ensure high-quality deliverables.
• Stay hands-on with critical aspects of system and model design, development, and validation to ensure robustness and scalability.
• Monitor and optimize performance of deployed systems, proactively identifying areas for improvement.
• Lead initiatives within the Data Engineering and Architecture practice area, contributing to capability building, asset development, and strategic growth.
  

Stay abreast of industry trends and advancements to maintain a competitive edge and drive continuous innovation.
Mandatory technical & functional skills

• Strong understanding of MPP databases and RDBMS fundamentals
• Hands-on experience with Cloud Platforms (SaaS/PaaS) preferably AZURE
• Expertise on cloud databases and Datawarehouse EG: AZURE SQL,SYNAPSE etc.
• Working knowledge with NoSQL databases EG: MongoDB,Cassandra,Redis
• In-Depth knowledge of SPARK ecosystem and APIs
• Exposure into Databricks and pySpark
• Clear understanding of datalakes and data lakehouses
• Decent understanding of Unity catalog, Delta live tables,MLFlow etc.
• Exposure into streaming
• Solid knowledge with building data pipelines using ADF,SYNAPSE,GLUE etc.
• Familiarity with Event Driven designs and messaging using service bus, Event grid
• Exposure into Serverless orchestrators EG: LogicApp,Function App,Airflow etc.
  

Familiarity with CI/CD using Git actions or AZURE devOps

Qualifications

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

• 7-9 years of experience in design, develop data centric applications using various tools and technologies e.g. Databases, reporting, ETL, NoSQL etc.
• 5+ years of experience in designing, architecting solutions using Microsoft Data technologies like ADF/SYNAPSE
• Relevant Data Professional certifications Databricks, AWS, GCP or Azure
  

#KGS