Snowflake Architect

<p><p><b>Description : </b><br/><br/><b>Role : Snowflake Architect (Lead Migration, Tech Debt, and MDM)</b><br/><br/>Experience Required : 10 - 15 years overall experience, with 5+ years in Snowflake architecture and large-scale data platform design<br/><br/><b>Role Overview : </b><br/><br/>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.<br/><br/><b>Key Responsibilities : </b><br/><br/>- Serve as the technical leader and architect across all Snowflake-related programs.

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

<br/><br/>- Define and implement data modeling, schema design, and performance optimization best practices.

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

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

<br/><br/>- Partner with the Program Manager to align delivery, scope, and cross-team dependencies.<br/><br/>- Mentor and guide data engineers and data scientists working across migration and enhancement pods.<br/><br/>- Collaborate on building the AI-ready semantic layer and integration with tools like NeoLens for conversational analytics.

<br/><br/>- Ensure scalability, cost optimization, and compliance across all Snowflake workloads.<br/><br/>- Participate in solution reviews, code walkthroughs, and technical governance.<br/><br/>- Act as a Snowflake thought leader advocating architecture patterns, best practices, and reusability across teams.<br/><br/><b>Required Skills & Experience : </b><br/><br/>- 1015 years of experience in data engineering and architecture.<br/><br/>- 5+ years of deep Snowflake design, performance tuning, and implementation experience.

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

<br/><br/>- Hands-on with SQL, Python, stored procedures, and Snowpark.

<br/><br/>- Understanding of ML model deployment workflows and integration with Snowflake.

<br/><br/>- Experience with AWS services (EC2, S3, Lambda, Step Functions).

<br/><br/>- Knowledge of security, governance, and role-based access in Snowflake.

<br/><br/>- Familiarity with Databricks and hybrid environments is an advantage.

<br/><br/>- Strong leadership and mentoring capabilities across engineering teams.</p><br/></p> (ref:hirist.tech)