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Tier-1 brand, metro location, and a popular Data Engineer title increase applicant competition.
Finance-platform focus and Snowflake/GenAI specialization increase domain-specific background sensitivity.
Explicit years, Snowflake expertise, finance-platform ownership and AI requirements create strict shortlisting filters.
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Design, build, and optimize Snowflake dimensional models and scalable ELT/ETL pipelines to support FS analytics platform.
Implement data quality checks, validation controls, and manage core Snowflake objects including performance tuning.
Leverage advanced Snowflake AI/ML features and AI tools to improve delivery and maintain competitive analytics capabilities.
5-10 years of professional experience with Snowflake and related technologies.
Expertise in SQL, data modeling, ETL/ELT, and building scalable data pipelines.
Experience with advanced Snowflake features: AI/ML, data sharing, materialized views.
Work Experience Required: At least 8 years relevant experience generally expected.
Proven expertise working at senior level on Snowflake platform with deep knowledge of dimensional modeling and data pipeline architecture.
Experienced using modern AI/ML techniques and AI assistants to enhance data engineering workflows.
Comfortable managing global, fast-paced environments balancing independent and collaborative work styles.