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
RESPONSIBILITIES
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
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
- 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
