Description

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

This role is on-site.

Responsibilities

• Define enterprise-wide data models, standards, and best practices for Snowflake environments.
• Architect modern data platforms supporting high-velocity financial data with scalability and sustainability.
• Optimize compute, storage, and processing costs while tuning performance for complex workloads.
• Build and standardize Data Development Platforms (DDP) to accelerate engineering productivity and automation.
• Mentor data engineers and guide teams on architecture patterns, design principles, and governance.

Required Skills

• 10+ years of experience in Data Engineering or Data Architecture with enterprise-scale systems.
• Extensive hands-on expertise in Snowflake architecture, implementation, and cost optimization.
• Strong experience in the financial services domain (banking, markets, or asset management).
• Deep understanding of data modeling (conceptual, logical, physical) and lakehouse patterns.
• Strong expertise in SQL and data performance tuning for large datasets.
• Experience designing and automating data marts, analytical layers, and data pipelines.
• Familiarity with modern data engineering tools such as dbt and orchestration frameworks.
• Proven ability to balance strategic planning with hands-on technical execution.

Preferred Skills

• Experience with AI-driven agents or automation frameworks to enhance solution efficiency.
• Background in modernizing legacy data platforms to cloud-native architectures.

Key Skills

Education

Any Gradute