The Senior Semantic Modeler will be responsible for designing, developing, and maintaining Semantic models using platforms like CubeDev, HoneyDew, AtScale, and others. This role requires a deep understanding of Semantic modeling principles and practices. The ideal candidate will work closely with data architects, data engineers, and business stakeholders to ensure the accurate and efficient representation of data for Generative AI and Business Intelligence purposes. Experience with graph- based semantic models is a plus.

Designation:

Product Architect - Semantic Modelling

Job Location:

Bangalore

Type of employment:

Permanent

Key Responsibilities:

Design and develop Semantic data models using any of the Semantic layer platforms such as CubeDev, HoneyDew, AtScale, etc.
Create and maintain Semantic layers that accurately represent business concepts and support complex querying and reporting.
Work closely with stakeholders to understand data requirements and translate them into semantic models.
Collaborate with data architects and engineers to integrate semantic models with existing Gen AI & BI infrastructure.
Ensure the semantic models align with business needs and support data governance policies.
Design & define key business metrics within the semantic models to ensure consistent and accurate reporting across the organization.
Collaborate with business stakeholders to identify and document metric definitions, ensuring clarity and alignment with business goals.
Develop and implement processes for metric validation and verification to ensure accuracy and reliability.
Monitor and maintain the performance of metrics within the Semantic models, addressing any issues or discrepancies promptly.
Develop and implement efficient queries and scripts for data retrieval and analysis.
Conduct regular reviews and updates of semantic models to ensure they remain current and effective.
Provide guidance and expertise on Semantic technologies and best practices to the development team.
Perform data quality assessments and implement improvements to ensure data integrity and consistency.
Stay up to date with the latest trends and advancements in Semantic technologies and incorporate relevant innovations into the modeling process.
Secondary responsibilities may include designing and developing graph- based semantic models using RDF, OWL, and other semantic web standards.
Create and maintain ontologies that accurately represent domain knowledge and business concepts.

Requirements:

Bachelors or Master s degree in Computer Science, Information Systems, Data Science, or a related field.
Minimum of 6+ years of experience in Semantic modeling, data modeling, or related roles.
Proficiency in any of the Semantic modeling platforms such as CubeDev, HoneyDew, AtScale, etc.
Strong understanding of data integration and ETL processes.
Familiarity with data governance and data quality principles.
Strong analytical and problem- solving skills.
Excellent communication and interpersonal skills.
Ability to work independently and as part of a team.
Experience with graph- based semantic modeling tools such as Prot g , Jena, or similar is a plus.

Functions skills:

Experience in Lifesciences commercial analytics industry is preferred and familiarity with industry- specific data standards.
Knowledge of Gen AI overview and frameworks would be plus.
Certification in BI semantic modeling or related technologies.

Qualifications

B. E Graduates are preferrable.

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Product Architect - Semantic Modelling