Snowflake Enterprise Data Architect

We are seeking a visionary and highly technical Snowflake Enterprise Data Architect to lead the strategy, design, and implementation of our next-generation enterprise data platform. In this role, you will be the principal architect responsible for transforming our data landscape into a scalable, secure, and high-performing ecosystem centered around Snowflake. You will bridge the gap between business strategy and technical execution, ensuring our data architecture supports advanced analytics, AI/ML initiatives, and seamless data democratization across the enterprise.

Key Responsibilities

• 1. Architecture & Strategy
  • Design & Strategy: Define the enterprise data architecture blueprint, roadmaps, and patterns using the Snowflake Data Cloud.
  • Data Modeling: Architect scalable conceptual, logical, and physical data models (Data Vault 2.0, Star/Snowflake Schema, 3NF) optimized for Snowflake's micro-partitioning and storage architecture.
  • Migration Leadership: Lead the architectural strategy for migrating legacy data warehouses (e.g., Teradata, Oracle, Netezza, or on-prem Hadoop) to Snowflake.
• 2. Implementation & Optimization
  • Performance Tuning: Optimize Snowflake performance through strategic warehouse sizing, clustering keys, materialized views, search optimization services, and query tuning.
  • Cost Management: Implement robust cost‑governance frameworks, resource monitors, and consumption tracking to ensure highly efficient utilization of Snowflake credits.
  • Data Integration (ETL/ELT): Design streaming and batch data ingestion pipelines using Snowpipe, Streams, Tasks, Kafka, and modern ELT tools (e.g., dbt, Matillion, Fivedran, or Airflow).
• 3. Governance, Security & Collaboration
  • Data Security & Compliance: Enforce rigorous data security policies within Snowflake, including Role‑Based Access Control (RBAC), Row‑Level Security (RLS), Column‑Level Security (CLS), data masking, and end‑to‑end encryption.
  • Data Sharing: Drive data monetization and collaboration strategies utilizing Snowflake Marketplace, private data exchanges, and clean rooms.
  • Cross‑Functional Collaboration: Partner with Data Engineers, Data Scientists, BI teams, and business stakeholders to translate complex business requirements into robust technical solutions.

Requirements

• Core Snowflake Mastery: Deep expertise in advanced Snowflake features (e.g., Snowpark, Iceberg tables, Dynamic Tables, Time Travel, Fail‑Safe, Zero‑Copy Cloning, and UDFs/Stored Procedures using Python/SQL).
• Cloud Ecosystems: Strong experience architecting cloud data solutions on at least one major cloud provider ( AWS, Azure, or GCP ) and integrating native services with Snowflake.
• Data Engineering & Code: Proficiency in SQL and Python or Scala. Strong grasp of software engineering best practices applied to data (CI/CD pipelines, Git, Terraform/DataOps).
• Data Governance: Familiarity with modern data governance and cataloging tools (e.g., Collibra, Alation, Apache Atlas).

Qualifications & Experience

• Experience: 10+ years of experience in data engineering, data warehousing, and enterprise data architecture, with at least 4+ years of dedicated experience designing production‑grade architectures on Snowflake .
• Proven Track Record: Successfully led at least two large‑scale enterprise data migrations from legacy systems to Snowflake.
• Education: Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or a related technical field (or equivalent professional experience).

Preferred Certifications

• Snowflake Certified Advanced: Data Architect (Highly Preferred)
• Snowflake Certified Core Professional
• Cloud Architect Certifications (e.g., AWS Certified Solutions Architect, Google Professional Cloud Architect, or Azure Solutions Architect Expert)