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.

The base salary range for this role is $134,300 - $229,400. The base salary range is
dependent on factors including, but not limited to, experience, skills, qualifications,
relevant education, certifications, seniority, and location. The range listed is just one
component of the total compensation package for employees. Other rewards vary by
position and location.

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.
• 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.
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.

COMPETENCIES:
People
• Building Effective Teams
• Developing Talent
• Collaboration
Self
• Leading by Example
• Communicates Effectively
• Ensures Accountability and Execution
• Manages Conflict
Business
• Business Acumen
• Plans, Aligns and Prioritizes
• Organizational Agility
With particular emphasis on the following specific position-related competencies:
• Technology Strategy & Innovation
• Stakeholder Engagement
• Data Architecture and Engineering
• Drive for Results

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. #LI-Hybrid

SUPERVISORY RESPONSIBILITIES:
N/A

DISCLAIMER:
This job description is a summary of the primary duties and responsibilities of the job and position.
It is not intended to be a comprehensive or all-inclusive listing of duties and responsibilities.
Contents are subject to change at management's discretion.