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Tier-1 brand and Bangalore location increase candidate competition despite senior specialization reducing pool.
Specialized data platform, graph, and AI skills are transferable but favor enterprise domain experience.
Multiple mandatory technologies and senior leadership expectations enforce strict technical filters.
Lead technical architecture and hands-on implementation of AI-ready data platforms including semantic data models, knowledge graphs, and intent-driven data access for private markets.
Own end-to-end design and sustainability of scalable data pipelines and analytics platforms using Snowflake, SQL, and Python.
Collaborate with stakeholders to translate strategic objectives into data initiatives, influencing technical prioritization and ensuring architectural coherence.
Proven senior technical experience with Snowflake, SQL, Python, and graph database technologies (e.g., Neo4j).
Experience designing semantic data models, ontologies, metadata-driven architectures, and AI-enabled data platforms.
Demonstrated leadership in technical roles, including leading complex initiatives and providing direction to engineers.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building AI-ready data platforms integrating vector databases, RAG architectures, and LLMs or AI agents.
Strong background in enterprise metadata management, data governance, pipeline tooling (Airflow, DBT), and cloud platforms (Azure or AWS).
Effective in technical stakeholder engagement and operating in fast-paced environments balancing strategic direction with delivery.