Data & Information Architect
On-siteHyderabad, Telangana, India
Job Summary
Design, develop, and deploy connected data solutions using information modeling, knowledge graphs, and generative AI to address high-value business and operational challenges. Build intelligent solutions that combine structured and unstructured data, semantic data models, and knowledge graph capabilities to improve automation, search, insight generation, and decision support. Develop and scale proof-of-concept solutions in SQL and SPARQL, transitioning them into robust, enterprise-ready data products. Apply SQL, R2RML, and data transformation techniques to analyze, integrate, and prepare data from multiple enterprise sources. Collaborate with business stakeholders, product teams, and domain experts to identify data use cases and translate requirements into scalable technical solutions. Integrate FAIR data principles and data-centric design practices with AI to promote interoperability and governance. Utilize Databricks and associated workflows to support experimentation and model verification with real-world data. Ensure alignment with responsible AI, security, privacy, and compliance expectations, including emerging regulatory frameworks like the EU AI Act. Facilitate working sessions with stakeholders to clarify concepts and define success criteria for transformation opportunities. Contribute to standards, reusable data products, and best practices for model-driven design and product scaling. Promote a culture of continuous improvement and innovation by identifying opportunities to improve current processes and ways of working. Stay current with advancements in knowledge graphs, context engineering, and agentic architectures, applying insights pragmatically within the organization.
Required Qualifications
- Master's degree OR Bachelor's degree with 4 to 7 years of experience in Data Science, Artificial Intelligence, Computer Science, Information Science, or related Functional Skills
- Strong hands-on experience in Information Modeling, Knowledge Graph development, and Generative AI, concepts and applications
- Proficiency in knowledge elicitation, data modeling for rapid prototyping, solution development, and scaling AI-driven capabilities
- Strong working knowledge of SQL for data analysis, transformation, and integration across enterprise systems
- Hands-on experience with Databricks or comparable data and AI platforms
- Strong understanding of integrated data, enterprise data ecosystems, and data-centric solution design
- Experience with knowledge graph and graph-based data platforms such as Stardog, GraphDB, or similar technologies
- Strong understanding of FAIR data principles and their application in enterprise and pharmaceutical data environments
- Ability to translate business concepts and requirements into models, semantic concepts, and data solutions
- Experience with regulatory data, regulatory submission processes, or compliance requirements in the pharmaceutical domain
- Familiarity with the pharmaceutical lifecycle of data, including development, manufacturing, regulatory, and operational domains
- Knowledge of data modeling and knowledge graph concepts
- Experience integrating data from sources such as clinical, laboratory, manufacturing, quality, or regulatory systems
- Familiarity with healthcare and life sciences standards such as FHIR, IDMP, or related interoperability frameworks
- Experience integrating data from sources such as clinical, laboratory, manufacturing, quality, or regulatory systems
- Exceptional interpersonal, communication, facilitation, and business analysis skills
- Strong analytical thinking and structured problem-solving skills, especially in complex and regulated environments
- Ability to manage ambiguity, think strategically, and convert emerging opportunities into practical solutions
- Strong ability to prioritize and manage multiple initiatives in a dynamic setting
- Demonstrated customer- and user-centric product design mindset
- Strong collaboration skills with cross-functional, global, and multidisciplinary teams
- Ability to influence without authority and build alignment across technical and business stakeholders
- Passion for continuous improvement, innovation, and transformation
- Strong ownership mindset with the ability to independently drive high-impact work from concept through implementation
Desired Qualifications
- Experience with regulatory data, regulatory submission processes, or compliance requirements in the pharmaceutical domain
- Familiarity with the pharmaceutical lifecycle of data, including development, manufacturing, regulatory, and operational domains
- Knowledge of data modeling and knowledge graph concepts
- Experience integrating data from sources such as clinical, laboratory, manufacturing, quality, or regulatory systems
- Familiarity with healthcare and life sciences standards such as FHIR, IDMP, or related interoperability frameworks
- Familiarity with product-oriented delivery and scaling data proofs of concept into operationalized enterprise capabilities
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