Data Architect (Snowflake) _ Onsite in Irvine, California _ 6 Months C2H _ LOCALS Preferred

Job Title

Data Architect

Rate

DOE

Location

Irvine, California

Duration

6 Months CTH (Local Candidates Preferred)

Priority

Urgent

Visa

Any VISA (Except H1B)

# Of Positions

1

Job Description

Senior Data Engineer, Data Architecture (Architect Track)

Location: Onsite in Irvine, CA

Department: AI Solutions & Cognitive Sciences

Reports to: Sr. Director, AI Solutions & Cognitive Sciences

About the role

The company is modernizing its enterprise data platform, moving toward a hybrid model that combines centrally governed infrastructure with domain-owned data products, built to be reliable enough for both traditional analytics and AI-driven analysis. This is a hands-on build role first: designing and shipping well-modeled pipelines in Snowflake, and making our data trustworthy enough for AI tools to reason over it without guessing.

As the program matures, this role is expected to grow into Data Architect, owning the modeling standard the organization builds to, and training teams across the business to publish their own well-governed data products.

What you'll do

In the first 6–12 months, hands-on:

• Design and build modern, layered data pipelines in Snowflake, replacing legacy reporting infrastructure and existing ETL processes with a cleaner, better-governed foundation
• Build flat, purpose-built data products for specific business domains, designed to be read reliably by both BI tools and AI, not just traditional reporting
• Implement and enforce data documentation standards using Snowflake's native data catalog and governance tooling: column-level tags, AI-generated descriptions, and clear data ownership on every table you ship
• Work directly with Snowflake's AI development tools to build and validate semantic models, and diagnose why AI-generated queries fail on poorly modeled data so future data products don't repeat it
• Partner with business subject matter experts across the organization to translate business logic into governed, well-documented data models
• Support the review process that determines whether a data product is ready for broader use

As the role grows into Data Architect:

• Own the enterprise data modeling standard and the criteria every team builds to
• Train and support engineers embedded across business teams, without becoming the only person who can do this work
• Make the calls on what's shared central infrastructure versus what each business domain owns and manages itself
• Represent data architecture to senior technology leadership
• Help evaluate how the data platform should evolve to support both simple, everyday questions and complex, cross-system analysis

What you'll need

• 5+ years of hands-on Snowflake experience, ideally within a broader 7–10-year data engineering career
• Master’s degree in computer science, Data Science, or a closely related field. A PhD is a plus but not a substitute for hands-on delivery, this role ships pipelines, it doesn't just design them
• Deep, current fluency with Snowflake's AI tooling: its code-generation, semantic modeling, and data catalog capabilities, not just core warehousing features
• Demonstrated ability to design AI-optimized data structures, flat, purpose-built, minimally joined models, not a default to traditional normalized star schema. You should be able to explain why a deeply joined model breaks AI-generated queries, not just that it does
• Strong SQL and at least one general-purpose language (Python preferred) for pipeline and tooling work
• Experience with modern ELT/ETL patterns and tooling
• Excellent written and verbal communication skills. You will need to explain architectural tradeoffs to engineers and to executives in the same week, and to get non-technical stakeholders to actually adopt a standard rather than route around it
• Comfort operating with real ambiguity: this org is evolving its data operating model, and some of what you'll own doesn't have a name yet

Nice to have

• SnowPro Advanced: Architect certification
• Experience standing up a data catalog or stewardship program from scratch, not just using one someone else built
• Exposure to RAG, agentic retrieval, or modern AI data-access patterns
• Experience mentoring or training engineers outside your own immediate team

Who you'll work with

You'll report into the AI Solutions & Cognitive Sciences team and work directly with engineers and subject matter experts embedded across business teams throughout the organization.