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Tier-1 brand, Mumbai metro, and popular Data Engineer title, but Snowflake specialization narrows the pool.
Core Snowflake and pipeline skills are transferable, but finance domain expertise increases specificity.
Explicit years plus mandatory Snowflake/SQL/Python and Snowflake AI skills create stringent filtering.
Design, maintain, and optimize Snowflake dimensional models and SQL transformations supporting the FS analytics platform revenue.
Develop and support ELT/ETL pipelines from multiple source systems including quality checks and validation controls.
Manage and improve Snowflake core objects and performance using advanced features including AI and Semantic Views for measurable delivery improvements.
5-10 years of professional experience with Snowflake and related technologies with strong SQL and data modeling skills.
Experience with Snowflake advanced features such as AI/ML integrations, data sharing, and materialized views.
Knowledge of Python for data processing (e.g., Pandas, NumPy) and familiarity with GenAI, LLMs, and AI assistant tools like GitHub Copilot or similar.
Work Experience Required: At least 8 years relevant experience expected; notice period: Not explicitly mentioned in the JD.
Experience operating at Director level with ownership of scalable, high-impact data platform components in financial services or technology-driven environments.
Strong technical expertise in Snowflake including advanced AI/ML features and practical adoption of generative AI tools in professional workflows.
Proven ability to independently improve platform performance and deliver measurable business value while supporting business growth and competitive positioning.