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Tier-1 brand and Bangalore metro raise competition, niche Databricks/agentic AI requirements moderate density.
Strong Databricks, cloud architecture, and agentic AI focus creates high domain-specificity and low cross-industry transferability.
Extensive mandatory Databricks, GCP/Azure, Airflow, Power BI, and agentic AI skills increase filtering strictness.
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Own end-to-end design and development of data and analytics products across platforms including data lakes, warehousing, BI, ETL pipelines, and AI-driven solutions.
Architect scalable, governed, and AI-ready data solutions leveraging Azure and GCP ecosystems to enable intelligent decision-making and advanced analytics.
Lead technical governance, ensure architecture alignment, and drive adoption of AI/ML and generative AI patterns including agentic AI and conversational analytics.
Strong hands-on expertise in Python, Databricks (Delta Lake, Unity Catalog), SQL/PostgreSQL, Apache Airflow, Power BI, GCP (including Cloud Run) and Azure ecosystems.
Proven experience architecting data solutions on GCP and Azure, including design and delivery of scalable enterprise systems.
Experience with AI/ML solution design including agentic AI frameworks and conversational AI (e.g., LangChain, AutoGen).
Work Experience Required: Not explicitly mentioned in the JD.
Technical leader with deep cross-cloud architecture expertise (Azure and GCP), data platform engineering experience, and AI/agentic AI solution know-how.
Operationally oriented, able to translate complex business requirements into modular, reusable, and production-grade technical architectures and code.
Experience in enterprise-scale data transformation/digital-first environments focusing on data lakes, lakehouses, BI, AI product lifecycle, and cloud migration initiatives.