We are seeking a highly skilled and motivated Consultant Data Modeler to design, develop, and support the maintenance of conceptual, logical, physical, and semantic data models that support advanced analytics, AI/ML, and Generative AI use cases.

The consultant will work closely with domain experts/business stakeholders, data science/engineering teams to translate complex business and system knowledge into scalable, high-quality data and semantic models. These models will serve as foundational assets enabling analytics, decision science, AI-driven insights, and intelligent automation across enterprise platforms. The role requires strong collaboration skills and the ability to work across multiple client environments.

Key Responsibilities :

Project and Team Leadership :

- Collaborate with business stakeholders and domain experts to understand data requirements and translate them into clear conceptual, logical, and physical data models.

- Work closely with data engineers, analytics teams, and AI/ML practitioners to ensure data models are aligned with downstream consumption needs.

- Aptitude to work independently on modeling workstreams within client engagements, including requirements gathering, design, and documentation.

- Document & communicate modeling decisions, trade-offs, and best practices to both technical and non-technical audiences.

- Contribute to project delivery through high-quality, low-defect delivery, documentation, design reviews, and model governance activities.

Data Modelling & Semantic Modelling Expertise :

- Design and maintain conceptual, logical, and physical data models for structured and semi-structured data across enterprise systems.

- Develop reusable, extensible data models supporting analytics, reporting, AI/ML feature engineering, and decision science use cases.

- Apply semantic modeling techniques, including domain modeling, entity relationships, hierarchies, and taxonomies.

- Enable ontology and knowledge graph modeling, translating subject-matter knowledge into machine-readable representations.

- Ensure alignment of data models with enterprise architecture principles, data standards, and best practices.

AI & GenAI Enablement :

- Design data and semantic models that act as foundational datasets for AI/ML and Generative

AI systems.

- Enable explainability, reasoning, and contextual grounding through ontology-driven

approaches and graph-based data models.

- Partner with data science and AI teams to ensure models support feature reuse, RAG

pipelines, and intelligent agent workflows.

- Contribute to data model designs that improve trust, interpretability, and scalability of AI-

driven solutions.

Data Governance & Standards :

- Follow and contribute to data modeling standards, naming conventions, and design guidelines across projects.

- Support data governance initiatives including metadata management, lineage, and documentation.

- Ensure consistency, quality, and reusability of data assets across platforms and use cases.

Business Impact and Innovation :

- Translate complex business concepts into clear, well-structured data models that accelerate analytics and AI adoption.

- Enable faster solution development by providing high-quality, well-documented data foundations.

- Support measurable outcomes by improving data usability, consistency, and decision-making effectiveness.

Job Qualifications :

Required Qualifications :

Experience :

- 4 - 6 years of experience with 3+ years of hands-on experience in data modelling, information modelling, or data architecture roles.

- Experience designing conceptual, logical, and physical data models.

- Experience working in consulting or client-facing roles is highly preferred.

Education :

- Bachelors or Masters degree in Computer Science, Data Science, Information Systems, Engineering, or a related field.

Technical Skills :

- Strong expertise in data modeling techniques and methodologies.

- Proficiency with data modeling tools (ER modeling tools, UML, or equivalent) is preferred.

- Experience working with relational and graph-based data models.

- Familiarity with semantic modeling concepts, ontologies, or knowledge graphs (e.g., RDF/OWL

concepts).

- Ability to collaborate effectively with data engineers, data scientists, and business

stakeholders.

Preferred Skills :

- Exposure to knowledge graph technologies (e.g., Neo4j or similar).

- Familiarity with AI/ML and GenAI consumption patterns, including feature stores, RAG

pipelines, and agentic systems.

- Experience defining data standards and governance frameworks.

- Prior experience supporting analytics, decision science, or AI-driven initiatives.

I have been with Accenture for more than five years and I like the diversified role that I play. By offering diversified roles, which gave me the opportunity to learn different processes other than my forte is the way Accenture groomed me into becoming a leader. I believe being a woman in this industry, one can contribute in creating a positive work environment and my one advice to all women consi...