Why This Job is Featured on The SaaS Jobs
Snowflake sits at the infrastructure layer of modern SaaS, where product capability and customer outcomes are tightly coupled to the quality of internal data platforms. A Data Architecture Lead in this context is notable because the remit spans governance, modeling standards, and access control in Snowflake itself, alongside practical adoption of AI-assisted workflows. The in-office expectation in Menlo Park also signals close partnership with product and engineering groups rather than a purely back-office data function.
For a SaaS career, this kind of principal-scope architecture role tends to compound in value because it builds fluency in how multi-team analytics and data engineering organizations scale. Work on RBAC patterns, row and column security, and deployment workflows translates across SaaS companies that operate regulated data, enterprise customers, or self-serve analytics. The emphasis on documentation, standards, and internal tooling also develops platform-thinking that is increasingly central as SaaS teams treat data capabilities as a product.
This role fits professionals who prefer influence through technical direction, operating across teams without direct authority, and balancing hands-on building with setting guardrails. It is likely best for someone comfortable being a visible point of reference for architecture decisions and for engaging externally when needed to explain patterns and tradeoffs.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
Founded by industry experts and backed by strategic investors, our disruptive built-for-the-cloud architecture was designed to push the limitations of conventional data warehousing. Our teams breed ambition, challenge ordinary thinking, and push the pace of innovation in service of the exploding demand for accessible data.
Snowflake is growing fast and we're scaling our team to help enable and accelerate our growth. We're passionate about our people, our customers, our values, and our culture! We're also looking for people with a growth mindset and the pragmatic insight to solve for today while building for the future. And as a Snowflake employee, you will be accountable for supporting and enabling diversity and belonging.
Snowflake started with a clear vision: make modern data warehousing effective, affordable, and accessible to all data users. Because traditional on-premises and cloud solutions struggle with this, Snowflake developed an innovative product with a new built-for-the-cloud architecture that combines the power of data warehousing, the flexibility of big data platforms, and the elasticity of the cloud at a fraction of the cost of traditional solutions.
We are looking for a Data Architecture Lead to join our Data, Analytics, and AI organization. This is a senior individual contributor role with principal-level scope. You will set the technical direction for how our data and analytics engineering teams build, govern, and evolve the data platform — and you'll be a hands-on practitioner who shapes what's possible.
This role an in office requirement - you must be able to work out of our Menlo Park office for a minimum of 3 days a week.
In This Role You Will
Define and deploy architectural standards across analytics and data engineering teams, covering data modeling patterns in dbt, RBAC frameworks, deployment workflows, and code quality standards
Build and deploy AI-powered tooling and skills — including agent frameworks, prompt-driven workflows, and LLM-enabled automation — for use across analytics and data engineering teams
Elevate the RBAC framework for the data platform, including designing and implementing row access policies, column masking policies, and role-based access control patterns at scale in Snowflake
Partner with Snowflake's product and engineering teams on feature testing and feedback — write meaningful product specifications, develop proof-of-concepts, and help push the Snowflake platform forward
Represent Snowflake's internal data capabilities externally, meeting with customers to demonstrate what is possible on the platform and sharing real-world architectural patterns and learnings
Act as a strategic lever across teams — bridging data engineering and analytics engineering to drive alignment, reduce redundancy, and raise the technical bar organization-wide
Enable the team through documentation, knowledge sharing, and mentorship — setting standards that scale beyond your own direct contributions
What You Will Need
Required
8+ years of experience in data engineering, analytics engineering, or data architecture roles
Deep expertise in Snowflake, including advanced data modeling, RBAC design, performance optimization, and the broader Snowflake feature set (Cortex, Dynamic Tables, Streams, Tasks, etc.)
Expert-level dbt skills (dbt Core and/or dbt Platform), including macro development, testing frameworks, CI/CD integration, and large-scale project management
Hands-on experience with Airflow or similar orchestration platforms for data pipeline management
Strong proficiency with AI development tools, including experience with LLM-powered workflows, agent frameworks (e.g., Cortex Agents, Claude Code, Cortex Code), and prompt engineering for data use cases
Experience designing and implementing RBAC frameworks at scale — including row access policies, masking policies, and role hierarchies in Snowflake or similar platforms
Excellent written and verbal communication skills, with a track record of writing clear technical specs, architecture documents, and stakeholder-facing materials
Ability to operate with principal-level scope: driving cross-functional initiatives, influencing without authority, and delivering outcomes across multiple teams
Preferred
Experience working at a technology company with a large-scale internal data platform
Prior experience building or contributing to internal developer tooling, shared libraries, or platform-as-a-product initiatives
Familiarity with Python for data pipeline development, scripting, and automation
Experience presenting technical content to external audiences (customers, conferences, etc.)
Snowflake is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, color, gender identity or expression, marital status, national origin, disability, protected veteran status, race, religion, pregnancy, sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.
Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
How do you want to make your impact?
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com
