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Tier-1 employer, popular Data Engineer role, and metro hiring increase candidate competition.
Highly domain-specific Snowflake and finance analytics experience required, limiting cross-industry transferability.
Explicit years plus mandatory Snowflake, SQL, Python, ELT/ETL and GenAI requirements raise strictness.
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Design and maintain Snowflake dimensional models and optimize SQL transformations and views for analytics and reporting.
Develop, support, and optimize ELT/ETL pipelines from multiple source systems.
Implement data quality controls, manage Snowflake core objects, and leverage AI tools to improve performance and delivery.
5-10 years of professional experience specifically with Snowflake and related data technologies.
Strong expertise in SQL, data modeling, ETL/ELT, and building scalable data pipelines.
Experience with advanced Snowflake features including AI/ML tools like Cortex Analyst/Agent, data sharing, and materialized views.
At least 8 years relevant experience overall.
Demonstrated ability to independently design and optimize complex data architectures in Snowflake for finance or analytics platforms.
Hands-on experience incorporating modern AI/ML applications and generative AI techniques to enhance data engineering workflows.
Comfortable working in a high-stakes, fast-paced global financial services environment with measurable impact on revenue through platform support.