Description

Lead the design and implementation of scalable, secure, and cost-optimized Snowflake data architectures for high-volume financial data.

This role is on-site.

Responsibilities

• Architect enterprise-wide data models, standards, and modern cloud-native data platforms supporting high-velocity financial data.
• Optimize Snowflake solutions by tuning compute, storage, and processing for large datasets and complex workloads.
• Build and standardize Data Development Platforms (DDP) to automate pipelines, data marts, and enable self-service capabilities.
• Lead legacy modernization initiatives, designing migration strategies and reusable patterns for enterprise adoption.
• Mentor data engineers and advise leadership on architecture strategy, governance, and security best practices.

Required Skills

• 10+ years of experience in Data Engineering or Data Architecture, focusing on enterprise-scale systems.
• Extensive hands-on expertise in Snowflake architecture, implementation, and cost optimization.
• Strong proficiency in SQL and data performance tuning for complex workloads.
• Deep understanding of data modeling (conceptual, logical, physical) and lakehouse patterns.
• Experience with Data Development Platforms (DDP) and engineering frameworks.
• Proficiency with modern data engineering tools, including dbt and orchestration tools.
• Proven track record in the financial services domain (banking, markets, or asset management).
• Ability to operate at both strategic planning and hands-on technical levels.

Preferred Skills

• Familiarity with AI-driven agents and automation frameworks to enhance solution efficiency.
• Experience leveraging AI tools to improve data ecosystem productivity.

Key Skills

Education

Bachelor's degree