Description

You will design and optimize large-scale data platform architectures using Snowflake for high-volume, low-latency financial workloads.

This role is on-site.

Responsibilities

• Architect and implement Snowflake solutions with deep expertise in performance tuning, virtual warehouses, clustering keys, and micro-partitioning.
• Develop and optimize Snowpark applications (Python/Java/Scala), including pushdown optimization, DataFrame operations, UDFs, and stored procedures.
• Design multi-region data distribution strategies and capacity models for 5x–10x volume projections, ensuring global data availability.
• Optimize semi-structured data handling using VARIANT columns, LATERAL FLATTEN, and materialized views for BI performance.
• Evaluate workload performance and metering using SNOWFLAKE.ACCOUNT_USAGE and INFORMATION_SCHEMA.

Required Skills

• 5+ years of hands-on Snowflake architecture experience.
• Expert proficiency in Snowpark (Python, Java, or Scala).
• Deep knowledge of Snowflake-specific features: Time Travel, Fail-safe, zero-copy cloning, and data sharing.
• Experience with financial services data domains: market risk, credit risk, P&L attribution, and multi-asset class models.
• Strong understanding of regulated environments, including PII handling and access control best practices.
• Proficiency in data engineering for high-volume, low-latency workloads.
• Familiarity with AWS, Azure, or GCP cloud infrastructure.

Preferred Skills

• SnowPro Core or Advanced Architect certification.
• Experience with BI tools (Sigma, Tableau, Power BI) connected to Snowflake.
• Background in professional services or advisory roles within financial technology.

Key Skills

Education

Bachelor's degree