Solution Architect II at Ross Stores, Inc.

Compensation

$134,300 – $229,400/yr

Setup: Remote, Hybrid
Location: Berkeley, California
Type: Full-time
Level: not_specified
Posted: Jul 1, 2026

Description

Ross Stores is seeking a highly motivated and visionary Solution Architect II to define, design, and govern enterprise-scale data solutions. This role focuses on building durable, scalable, and adaptable data architectures to power analytics, business intelligence, and AI-driven decision-making. The Solution Architect will partner with IT leaders, Data Engineering teams, and Business Analytics/Information functions to translate complex business needs into flexible data architectures.

Required Skills

data architecture
solution architecture
software engineering
enterprise-scale data solutions
cloud and hybrid data platforms
data architecture patterns
analytical data stores
ELT frameworks
transformation pipelines
semantic modeling
Snowflake
dbt
Alation
Streamsets
MicroStrategy
Power BI
FinOps principles
BI, reporting, and advanced analytics capabilities
AI/ML data requirements
advanced analytics, feature engineering, and model operations
communication and leadership skills

Additional Information

Required Previous Experiences: 7+ years of experience in Data Architecture, Solution Architecture, and/or software engineering.
Preferred Qualifications: Extensive experience architecting enterprise-scale data solutions across modern cloud and hybrid data platforms.
Deep understanding of data architecture patterns including analytical data stores, ELT/ETL frameworks, transformation pipelines, and semantic modeling.
Hands-on working knowledge of Snowflake, dbt, Alation, Streamsets, MicroStrategy, Power BI and related modern Data Technologies.
Strong understanding of FinOps principles with proven experience in Snowflake cost management, usage governance, and consumption optimization.
Proven experience enabling BI, reporting, and advanced analytics capabilities across large organizations.
Ability to design flexible, future-ready architectures that remain adaptable as tools, vendors, and technologies evolve.
Working knowledge of AI/ML data requirements and the architectural components needed to support advanced analytics, feature engineering, and model operations.
Strong communication and leadership skills with the ability to influence senior technical leaders, business stakeholders, and cross-functional teams.