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. 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.

Base salary range: $134,300 – $229,400.

• 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.

• Building Effective Teams
• Developing Talent
• Collaboration

• Leading by Example
• Communicates Effectively
• Ensures Accountability and Execution
• Manages Conflict

• Business Acumen
• Plans, Aligns and Prioritizes
• Organizational Agility

• Technology Strategy & Innovation
• Stakeholder Engagement
• Data Architecture and Engineering
• Drive for Results

• Bachelor's degree in information systems, computer science, or a related technical discipline. Master’s degree is a plus.
• Minimum 7…