Snowflake Data Architect

Job Summary:

We are looking for a highly experienced Senior Snowflake Data Architect to drive the design and evolution of large-scale, enterprise data platforms in a data-intensive environment. This role requires a strategic thinker and hands-on architect who can solve complex, real-world data challenges, optimize for cost and performance, and design future-ready data ecosystems.

The ideal candidate will have deep expertise in Snowflake architecture, strong experience with financial domain data, and a proven ability to design scalable, efficient, and resilient data solutions. This individual will play a key role in shaping enterprise data strategy, enabling advanced analytics, and modernizing legacy systems.

Key Responsibilities

Architecture & Design

• Lead the design and development of scalable, secure, and high-performing Snowflake-based data architectures.
• Define and implement enterprise-wide data models, data standards, and best practices.
• Architect modern data platforms supporting high-volume, high-velocity financial data.
• Design future-ready data ecosystems, ensuring scalability, flexibility, and long-term sustainability.

Problem Solving & Optimization

• Solve complex, large-scale data challenges in a high-volume enterprise environment.
• Design cost-effective Snowflake solutions, optimizing compute, storage, and data processing.
• Implement performance tuning strategies for large datasets and complex workloads.
• Drive architectural decisions balancing cost, performance, and data accessibility.

Data Platform & Engineering Enablement

• Build and standardize Data Development Platforms (DDP) to accelerate engineering productivity.
• Design frameworks for automating data pipelines and data marts at scale.
• Enable self-service data capabilities while maintaining governance and control.

Modernization & Transformation

• Lead initiatives to modernize legacy data platforms and transition to cloud-native architectures.
• Design approaches for data migration, transformation, and integration across systems.
• Establish reusable patterns and frameworks for enterprise-wide adoption.

Leadership & Strategy

• Act as a trusted advisor to leadership on data architecture and platform strategy.
• Proactively identify opportunities and recommend innovative solutions.
• Mentor data engineers and guide teams on best practices, architecture patterns, and design principles.
• Collaborate with multiple stakeholders including engineering, analytics, governance, and business teams.

Innovation & Automation

• Leverage modern tools, automation frameworks, and AI-driven agents to enhance productivity and solution efficiency.
• Continuously evaluate new technologies and tools to improve the data ecosystem.

Required Skills & Qualifications

• 10 years of experience in Data Engineering / Data Architecture, with a strong focus on enterprise-scale systems.
• Extensive hands-on expertise in Snowflake architecture and implementation.
• Strong experience in financial services domain (banking, markets, asset management, etc.).
• Proven experience designing cost-optimized, high-performance cloud data platforms.
• Deep understanding of:
  • Data architecture principles
  • Data modeling (conceptual, logical, physical)
  • Data warehousing and lakehouse patterns
• Experience with Data Development Platforms (DDP) and engineering frameworks.
• Strong expertise in SQL and data performance tuning.
• Experience designing and automating data marts and analytical layers.
• Familiarity with modern data engineering tools (e.g., dbt, orchestration tools, etc.).
• Strong understanding of scalability, governance, and security in enterprise data systems.
• Ability to operate at both strategic and hands-on technical levels.