Key Responsibilities

• Platform Architecture: Define and scale cloud-native architectures that interface with Snowflake and AWS or Azure cloud platforms.
• Data Modeling & Pipelines: Design high-volume relational and complex data models capable of handling real-time streaming and batch ingestion.
• Governance & Performance: Implement advanced Snowflake features like RBAC (Role-Based Access Control), virtual warehouse sizing, micro-partitioning, query profiling, and zero-copy cloning.
• Financial Data Domains: Architect data flows specific to investment firms (e.g., trade lifecycles, Benchmarks, Cash, Transactions, and Performance).
• Cloud & DevOps Integration: Collaborate on CI/CD pipelines, automated testing, and data lakehouse or streaming interoperability (e.g., using Databricks, dbt, Apache Airflow).
• AI & Advanced Analytics: Leverage built-in Snowflake machine learning capabilities (like Snowflake Cortex AI) to supplement and automate human-based data validation.
• Typical Qualifications & Experience
• Experience: 10+ years in enterprise-scale cloud engineering, data platform engineering, or solution architecture, with 5+ years specifically focused on Snowflake development.
• Industry Knowledge: Deep expertise in financial services data domains. Prior experience with OMS platforms (like Charles River Development or Aladdin) is typically highly preferred.
• Technical Skills: Advanced SQL, hands-on experience with ETL/ELT pipelines, and cloud-native integration paradigms.