Snowflake Architect

3 days ago

Gurgaon, Haryana, India DHI Solutions Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Description
Role : Snowflake Architect (Lead Migration, Tech Debt, and MDM)
Experience Required : 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.

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