Data Architect

We are seeking an experienced Data Architect (4+ years) to lead the design and evolution of our Snowflake data platform. You will own the \"big picture\" architecture, ensuring data models are scalable, secure, and performant, while defining standards for data modeling, ELT (dbt), and Python-based integrations. You will collaborate with Data Engineers and Admins to align technical execution with long-term architectural goals.

Platform Architecture: Lead end-to-end Snowflake architecture. Design scalable data layers (Raw, Staging, Marts) to support future growth.

Data Modeling: Define and enforce best practices (Star Schema, Data Vault, OBT).

dbt Architecture: Structure dbt projects; set standards for macros, incremental strategies, and materializations for efficient transformation.

Technical Leadership: Mentor the team, review code, design complex SQL/Python patterns, and ensure CI/CD/DevOps best practices.

Python/Snowpark: Architect solutions using Snowpark (Python 3.10/3.11) for advanced analytics, ML integration, and complex transformations.

Data Governance & Quality: Implement observability, quality testing, lineage, and compliance frameworks.

Optimization: Evaluate system performance, re-architect inefficient flows, and apply clustering/partitioning to optimize cost and speed.

• Experience: 4+ years in Data Architecture, Data Engineering, or technical leadership.
• Snowflake Expertise: Deep knowledge of architecture, micro-partitions, clustering, warehouse sizing, and cost optimization.
• Data Modeling: Proven ability to design complex operational and analytical models.
• dbt: Experience managing large-scale dbt projects with performance and maintainability in mind.
• Cloud: Solid understanding of cloud platforms (AWS, Azure, GCP) and Snowflake integration (IAM, networking, storage).
• Communication: Ability to translate technical concepts into business value.

• Experience with Data Mesh or Data Lakehouse architectures
• Experience with streaming data (e.g., Snowpipe Streaming)