Solution Architect II

General Purpose

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.

Essential Functions

• Enterprise Data Architecture & Strategy
• 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.
• Evaluate emerging technologies and guide platform choices based on business fit, scalability, sustainability and cost.
• Leadership & Influence
• 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.
• Data Transformation, Modeling & Analytics Enablement
• 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.
• Data Integration & Lifecycle Design
• 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.
• AI & Advanced Analytics Readiness
• 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.
• Data Platform, Governance, Metadata & Trust
• 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.

Qualifications and Special Skills Required

• Bachelor's degree in information systems, computer science, or a related technical discipline. Master's degree is a plus.
• 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.

Physical Requirements/ADA

Job requires ability to work in an office environment, primarily on a computer. Requires sitting, standing, walking, hearing, talking on the telephone, attending in-person meetings, typing, and working with paper/files, etc. Consistent timeliness and regular attendance. Vision requirements: Ability to see information in print and/or electronically. This role requires regular in-office presence, including to engage in in-person team interaction, meetings and collaboration, mentoring, coaching, and/or feedback. However, this role can perform duties effectively using a combination of in-office and remote work.

Supervisory Responsibilities

N/A