Description :

Role : Snowflake Architect (Lead Migration, Tech Debt, and MDM)

Experience Required : 10 - 15 years overall experience, with 5+ years in Snowflake architecture and large-scale data platform design

Role Overview :

We are seeking a Senior Snowflake Architect to lead Snowflake initiatives across multiple strategic programs - Databricks migration, Tech Debt reduction, MDM enablement, and AI readiness. The role requires deep hands-on Snowflake expertise, architectural vision, and the ability to guide multiple pods of engineers and data scientists toward scalable, secure, and optimized implementations.

Key Responsibilities :

- Serve as the technical leader and architect across all Snowflake-related programs.

- Design, architect, and oversee the migration of ML and analytical workloads from Databricks to Snowflake.

- Define and implement data modeling, schema design, and performance optimization best practices.

- Lead the Tech Debt Tiger Squad to streamline data quality, governance, and security within Snowflake.

- Define the MDM (Master Data Management) framework leveraging Snowflakes data sharing, governance, and lineage capabilities.

- Partner with the Program Manager to align delivery, scope, and cross-team dependencies.

- Mentor and guide data engineers and data scientists working across migration and enhancement pods.

- Collaborate on building the AI-ready semantic layer and integration with tools like NeoLens for conversational analytics.

- Ensure scalability, cost optimization, and compliance across all Snowflake workloads.

- Participate in solution reviews, code walkthroughs, and technical governance.

- Act as a Snowflake thought leader advocating architecture patterns, best practices, and reusability across teams.

Required Skills & Experience :

- 1015 years of experience in data engineering and architecture.

- 5+ years of deep Snowflake design, performance tuning, and implementation experience.

- Strong knowledge of data pipelines, ETL frameworks (DBT, Airflow), and data modeling (Kimball/Inmon).

- Hands-on with SQL, Python, stored procedures, and Snowpark.

- Understanding of ML model deployment workflows and integration with Snowflake.

- Experience with AWS services (EC2, S3, Lambda, Step Functions).

- Knowledge of security, governance, and role-based access in Snowflake.

- Familiarity with Databricks and hybrid environments is an advantage.

- Strong leadership and mentoring capabilities across engineering teams.