Sr. Data Architect

YETI•Austin, TX

About The Position

At YETI, we believe that time spent outdoors matters more than ever and our gear can make that time extraordinary. When you work here, you’ll have the opportunity to create exceptional, meaningful work and problem solve with innovative team members by your side. Together, you’ll help our customers get the high-quality gear they need to make the most of their adventures. We are BUILT FOR THE WILD™. At YETI, we believe that time spent outdoors matters more than ever and our gear can make that time extraordinary. When you work here, you’ll have the opportunity to create exceptional, meaningful work and problem solve with innovative team members by your side. Together, you’ll help our customers get the high-quality gear they need to make the most of their adventures. We are BUILT FOR THE WILD™. The Data Architect is responsible for defining, designing, and governing the Enterprise Data Warehouse (EDW) architecture on Google BigQuery, enabling scalable, high-performance analytics, reporting, and data products across the enterprise. This role partners closely with Data Engineering, Analytics, Product, and Business teams to translate business needs into a governed, cost-efficient, and future-ready data architecture. The ideal candidate brings deep expertise in BigQuery-based EDW design, dimensional and semantic modeling, data governance, and enterprise-scale analytics platforms in a cloud-native environment.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent experience.
8+ years of experience in data architecture, data warehousing, or analytics platforms.
Strong hands-on expertise with Google BigQuery in an enterprise EDW context.
Deep knowledge of data modeling (dimensional, star schema, analytical modeling).
Advanced SQL expertise for analytical and transformation workloads.
Experience designing enterprise-scale EDW platforms supporting BI and analytics.
Strong understanding of data governance, data quality, and security concepts.
Excellent communication and stakeholder management skills.

Nice To Haves

Experience with GCP ecosystem (BigQuery, Cloud Storage, Dataflow, DataProc, Composer).
Experience integrating data from ERP (SAP), eCommerce, Marketing, and Supply Chain systems.
Familiarity with BI semantic modeling and enterprise reporting architectures.
Experience supporting self-service analytics at scale.
Prior experience in retail, consumer goods, or omnichannel businesses is a plus.

Responsibilities

Define and own the EDW reference architecture on Google BigQuery, including datasets, schemas, layering (staging, curated, reporting), and access patterns.
Establish data modeling standards (dimensional, star/snowflake, wide tables, aggregated views) to support BI, analytics, and downstream consumption.
Design semantic and reporting layers that support governed self-service analytics and enterprise reporting.
Lead logical and physical data model design for core enterprise domains (e.g., customer, product, orders, finance, supply chain).
Ensure models are optimized for BigQuery performance, partitioning, clustering, and cost efficiency.
Define standards for reusable dimensions, facts, and cross-domain conformed models.
Partner with Data Engineering teams to architect ELT/ETL patterns leveraging BigQuery SQL transformations and cloud-native ingestion.
Provide architectural guidance for ingestion from enterprise systems (e.g., SAP, eCommerce platforms, APIs, file-based feeds).
Ensure architectural alignment across batch and near-real-time data pipelines.
Define and enforce data governance, data quality, and metadata standards across the EDW.
Partner with data governance and security teams to implement data access controls, privacy, and compliance within BigQuery.
Drive consistent definitions, KPIs, and certified datasets across the enterprise.
Enable BI and analytics platforms (e.g., Power BI, Tableau, Looker) through well-designed BigQuery datasets and semantic models.
Ensure EDW architecture supports enterprise reporting, ad-hoc analytics, and advanced analytics use cases.
Define and monitor BigQuery cost optimization strategies, including query optimization, dataset design, and workload isolation.
Ensure the EDW scales to support growing data volumes, users, and analytical complexity.
Act as the architectural authority for EDW design decisions.
Collaborate with architects, engineers, analytics teams, and business stakeholders.
Provide architectural guidance, reviews, and mentoring to data engineers and analysts.