Principal Data Platform Engineer / Architect

Avenue 45; Irvine (CA); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Avenue 45 is seeking a Principal Data Platform Architect in hybrid Irvine, CA. This role centers on Snowflake platform architecture, enterprise data strategy, and governance across lakehouse layers.

You will drive cross-functional collaboration to align business needs with technical data platform solutions, enabling self-service analytics and AI-enabled pipelines at scale.

Qualifications

• Deep Snowflake expertise is required and hands-on platform architecture experience is essential.
• Experience designing enterprise data platforms, lakehouse architectures, and governance standards.
• Proven ability to translate business needs into technical architecture and data platform solutions.

Responsibilities

• Define and own enterprise data platform strategy and roadmap.
• Design Snowflake-based Lakehouse architecture and bronze/silver/gold models.
• Lead integration architecture and patterns (API-led, event-driven, batch).
• Architect semantic layers, governed datasets, and self-service BI enablement.
• Partner with data science teams on MLOps and AI platform foundations.

Skills

Deep Snowflake expertise

Translate business needs into tech

Platform strategy leadership

Lakehouse/medallion architectures

Self-service BI governance

Communication with executives

Strategic thinking

Education

Bachelor's degree in CS/IS/Data Eng

Master's degree preferred

Tools

Snowflake

Fivetran

dbt

Job description

Work Arrangement:

Hybrid 3 days week onsite

Location:

Irvine, CA

Please Note:

Snowflake specifically, which is a key focus of this role. The client is looking for stronger examples of translating business needs into technical solutions and platform strategy.

This is not just a broad Data Architecture/Cloud Modernization role. The person needs deep, hands-on Snowflake platform architecture experience and must be able to connect business requirements to the technical platform strategy.

What Client is Looking For:

• Deep Snowflake expertise is required — this is a key focus of the role.
• Strong hands-on experience with Snowflake, Fivetran, dbt, and semantic modeling.
• Proven ability to translate business needs into technical architecture and data platform solutions.
• Experience defining enterprise data platform strategy, architecture, standards, and roadmaps.
• Candidates should demonstrate specific platform architecture experience, not solely broad data architecture or cloud transformation experience.

Education

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field required.
• Master's degree in Computer Science, Information Management, or Business/Technology discipline preferred.

Experience

• 10+ years of experience in data architecture, data engineering, or enterprise data platforms.
• 5+ years in a senior/lead architect role driving platform strategy, standards, and governance at enterprise scale.
• Proven expertise designing and operating cloud-based data platforms Snowflake, including Lakehouse/medallion architectures.
• Hands-on experience with ELT/ETL tools, data modeling, and metadata management (dbt, Fivetran, or comparable).
• Strong background in enterprise integration (API-led, event-driven, or batch patterns).
• Demonstrated success enabling self-service BI and analytics platforms with governed semantic layers. Exposure to machine learning/AI platforms and MLOps practices for operationalizing models. Track record of partnering with business leaders to align data platforms with strategic business needs (growth, efficiency, compliance, innovation).
• Excellent leadership, communication, and stakeholder management skills; experience influencing technical and executive audiences.

Knowledge and Skills:

• Data Architecture & Modeling – Expert in designing Lakehouse architectures (bronze/silver/gold) and enterprise data models that support both analytics and AI/ML workloads.
• Cloud Data Platforms – Deep hands-on knowledge of Snowflake (or equivalent cloud-native platforms), including performance tuning, cost optimization, multi-tenant design, and governance.
• Data Engineering & ELT – Strong proficiency in dbt or similar transformation frameworks, ELT/ETL orchestration, metadata management, and automation of data pipelines.
• Integration Patterns – Advanced understanding of API-led, event-driven, and batch integration; skilled at designing reusable integration frameworks.
• Analytics & BI Enablement – Skilled at architecting self-service BI environments, semantic layers, and governed datasets; experience with enterprise BI tools.
• Machine Learning & AI Enablement – Familiarity with ML pipelines, feature stores, and MLOps practices to operationalize AI models.
• Security, Compliance & Governance – In-depth knowledge of data security, privacy, and governance frameworks, including RBAC/ABAC models and regulatory compliance.
• Leadership & Communication – Strong ability to translate complex technical concepts into business value, influence senior executives, and guide cross-functional teams.
• Strategic Thinking – Ability to balance long-term platform vision with short-term delivery, ensuring scalability, adaptability, and cost-effectiveness.

Position Summary:

The Principal Data Platform Architect defines and drives the company's enterprise data platform strategy and roadmap. This role designs a modern Lakehouse architecture on Snowflake, enables self-service BI, advances integration across systems and data domains, and establishes the foundation for machine learning and AI platforms—ensuring the ecosystem is scalable, secure, and delivers trusted data for business value.

Major Duties and Responsibilities:

Define and own the enterprise data platform strategy and roadmap:

• Develop the architectural vision for data, integration, analytics, and AI platforms.
• Align platform capabilities with evolving business needs such as growth, efficiency, compliance, and innovation.
• Establish architectural principles, standards, and governance.
• Design and govern Snowflake-based Lakehouse architecture (medallion model):
• Design the logical data models for bronze, silver, and gold layers.
• Ensure data quality, lineage, and security across structured and semi-structured data.
• Optimize performance, cost management, and multi-tenant scalability.
• Lead integration architecture across systems and data domains:
• Define patterns for API-led, event-driven, and batch data movement.
• Standardize error handling, monitoring, and metadata capture.
• Ensure interoperability between enterprise applications, data warehouse, and operational platforms. Enable and expand self-service BI and analytics:
• Architect semantic layers and governed datasets for analytics platforms.
• Define policies for certified vs. exploratory analytics.
• Deliver frameworks for data catalogs, data dictionaries, and end-user guides.
• Lay the foundation for machine learning and AI platforms:
• Ensure data pipelines support ML feature engineering and model training.
• Partner with data science teams to establish MLOps best practices.
• Enable reuse of data assets for predictive and generative AI use cases.

Candidates must be legally authorized to work in the United States without current or future employer sponsorship.

Must be able to pass and clear background check, Drug, education and employment verification and/or references prior to starting.