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Tier-1 employer, Bangalore location, and broad multi-cloud plus AI skill requirements increase competition.
Skills transferable across industries, but enterprise-scale Databricks, GCP, and agentic-AI experience increases domain specificity.
Multiple mandatory hands-on skills across Databricks, GCP, Python, Airflow, and BI drive high shortlisting strictness.
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Own end-to-end design and architecture of scalable data and analytics platforms within the Data Foundation ecosystem, covering data lakes, warehouses, BI/reporting, ETL pipelines, and AI solutions.
Lead integration of cloud platforms (Azure and GCP) and AI/ML frameworks including agentic and generative AI to deliver data products driving intelligent decision-making.
Partner with business stakeholders to translate requirements into technical designs, ensuring solutions are cost-efficient, governed, secure, and deliver measurable business impact.
Strong hands-on experience in Python programming for production data and AI solutions.
Proven expertise in Databricks ecosystem (Delta Lake, Unity Catalog, orchestration) and advanced skills in SQL/PostgreSQL.
Significant experience with Google Cloud Platform (including Cloud Run) and Azure ecosystems (ADF, Azure SQL).
Work Experience Required: Not explicitly mentioned in the JD.
Deep knowledge of modern cloud data architectures including lakehouse, warehouse, and multi-cloud interoperability (Azure + GCP).
Experienced in architecting AI/ML and agentic AI solutions with hands-on skills in LangChain, RAG, conversational AI frameworks.
Proven ability to drive enterprise-scale data platforms end-to-end, balancing technical excellence with product alignment and governance in fast-evolving environments.