Solution Architect II

Ross Stores • Dublin, CA

2d • $134,300 - $229,400 • Hybrid

About The Position

We are seeking a highly motivated and visionary Solution Architect to serve as a senior technical leader responsible for defining, designing, and governing enterprise-scale data solutions that power analytics, business intelligence, and AI‑driven decision-making. This role focuses on building durable, scalable, and adaptable data architectures that support today’s requirements while providing a foundation for future technologies and business growth. Operating at both strategic and enterprise levels, the Solution Architect partners closely with IT leadership, Data Engineering teams, and Business Analytics/Information functions to translate complex business needs into flexible data architectures—ensuring long-term value, interoperability, and extensibility across evolving platforms and tools.

Requirements

• Bachelor’s degree in information systems, computer science, or a related technical discipline.
• Minimum 7 years of experience in Data Architecture, Solution Architecture and/or software engineering roles.
• 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, including how these tools integrate into enterprise data ecosystems.
• 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.

Nice To Haves

• Master’s degree is a plus.

Responsibilities

• Define and own enterprise data architecture principles and standards that are independent of specific vendors or platforms.
• Design end-to-end data solutions that support analytical, operational, and advanced analytics use cases.
• Establish architectural patterns for data ingestion, storage, transformation, modeling, and consumption.
• Evaluate emerging technologies and guide platform choices based on business fit, scalability, sustainability and cost.
• Act as a trusted advisor to IT and Business leadership on data strategy, modernization, and investment decisions.
• Lead architecture reviews and provide direction on complex, cross-domain data initiatives.
• Mentor architects, engineers, and analytics practitioners on modern, vendor-agnostic data architecture practices.
• Influence enterprise alignment through architectural guidance rather than direct authority.
• Architect analytics-ready data pipelines using modern transform-centric data approaches (e.g., ELT).
• Define enterprise data models and semantic abstractions that can be reused across analytics and reporting tools.
• Enable both standardized reporting and self-service analytics across multiple BI and visualization platforms.
• Ensure analytical solutions remain portable, maintainable, and not tightly coupled to a single toolset.
• Define integration patterns for ingesting data from diverse internal and external sources.
• Support batch and near real time processing scenarios through flexible architectural designs.
• Establish expectations for data quality, observability, resilience, and lifecycle management.
• Promote loosely coupled architectures that support change and growth.
• Identify and shape AI and advanced analytics use cases, such as forecasting, optimization, anomaly detection, and decision intelligence.
• Ensure data architectures support AI/ML needs, including feature readiness, experimentation, and scalable consumption.
• Partner with Data Science and Analytics teams to align data foundations with evolving analytical and AI capabilities.
• Advise leadership on architectural readiness for emerging AI enabled applications without locking into specific platforms.
• Partner with Data Governance teams to implement enterprise metadata management, data lineage, and stewardship processes.
• Ensure architectures support discoverability, ownership, and trust in enterprise data assets.
• Align data solutions with security, privacy, and compliance requirements across regulatory environments.
• Promote documentation, standards, and shared accountability for data quality.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior