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Tier-1 brand, Mumbai, generalist Snowflake data engineer with broad skills yields high applicant competition.
Snowflake and data-engineering skills are transferable, but finance platform experience increases domain specificity moderately.
Senior Director-level years plus mandated Snowflake, ELT, Python, and GenAI skills create strict shortlisting.
Develop and maintain Snowflake dimensional models and optimize SQL transformations for analytics and reporting.
Build and support ELT/ETL pipelines from multiple source systems including implementing data quality and validation controls.
Manage and improve Snowflake performance through resource optimization, query profiling, and advanced feature usage including AI-driven tools.
5-10 years professional experience in Snowflake and related technologies.
8 years relevant work experience generally expected for this director-level role.
Proficiency in SQL, Snowflake advanced features (AI/ML, data sharing, materialized views), and Python data processing libraries.
Work Experience Required: 5-10 years in Snowflake technology and relevant data engineering domain.
Experienced in designing Snowflake dimensional data models and advanced Snowflake cloud features to enhance data platform performance.
Capable of leveraging AI tools (e.g., GitHub Copilot, Snowflake AI features) to drive practical improvements in data engineering workflows.
Able to operate independently and collaboratively in a fast-paced global finance technology environment with strong communication skills.