Bachelor's degree in Computer Science, Analytics, or related field; Master's preferred
10+ years of experience in data modeling, analytics engineering, or data architecture
Experience setting enterprise-wide data modeling or semantic layer standards
Extensive hands-on expertise with Snowflake or comparable cloud data warehouse architecture, semantic layers, and SQL
dbt Analytics Engineering Certification and Snowflake SnowPro Core Certification preferred
Responsibilities
Define and own the semantic layer strategy and architecture across all domains
Set enterprise-wide data modeling standards and technology choices for Analytics Engineering
Evaluate and select tools for the semantic/analytics layer, considering cost and scalability
Identify and resolve cross-domain architectural risks or inconsistencies
Partner with the Data Architect for platform and analytics layer alignment
Advise on long-term analytics architecture strategy
Establish frameworks for data quality, observability, and governance
Serve as the final technical escalation point for complex modeling problems
Mentor junior team members on architectural thinking
Benefits
Flexible working hours, including nights and weekends as needed
Opportunity for overtime and holiday work
Travel between offices as required
Pre-employment testing required
Legally eligible to work in the U.S.
Full Job Description
As a member of the Data and Analytics team, the Analytics Architect responsibilities will fall between data engineering and the business, turning raw, well-structured data into governed, business-friendly semantic models - the layer that both self service tools and analysts depend on for accurate, consistent answers. This role owns the semantic layer strategy and architecture across all business domains. This role sets enterprise-wide modeling standards and technology direction, resolves cross-domain architectural risks, partners with the Data Architect on platform alignment, and mentors junior team members on architectural thinking.
Responsibilities of Position:
Define and own the semantic layer strategy and architecture across all domains, ensuring consistency as new domains and use cases are added
Set enterprise-wide data modeling standards, patterns, and technology choices for Analytics Engineering, influencing adoption across the team without direct management authority
Evaluate and select tools and technologies for the semantic/analytics layer, weighing cost, scalability, and long-term maintainability Identify cross-domain architectural risks or inconsistencies before they compound, and drive resolution across multiple domains
Partner with the Data Architect to ensure alignment between platform architecture and analytics/semantic layer architecture
Advise team leadership on long-term analytics architecture strategy, including how today's decisions affect future scalability and flexibility
Establish frameworks for data quality, observability, and governance that apply consistently across all domains
Serve as the final technical escalation point for complex, cross-domain modeling problems
Mentor junior team members on architectural thinking, not just modeling execution
Perform other duties as assigned
Supervisory Responsibility:
This position will not manage employees
Skills & Abilities Needed for Position:
Excellent analytical and problem-solving skills
Ability to resolve ambiguous or conflicting requirements independently
Ability to mentor and review the work of less experienced team members
Ability to drive alignment and prioritization across multiple stakeholders and competing priorities
Excellent written and verbal communication skills
Ability to diagnose root causes of data or reporting issues, not just identify symptoms
Experience & Knowledge Needed for Position:
Bachelor's degree in Computer Science, Analytics, or related field required; Master's degree a plus
10+ years of experience in data modeling, analytics engineering, or data architecture required
Experience setting enterprise-wide data modeling or semantic layer standards required
Extensive hands-on expertise with Snowflake or a comparable cloud data warehouse architecture, semantic layers, and SQL required
dbt Analytics Engineering Certification and Snowflake SnowPro Core Certification preferred
Physical Requirements in a Regular Workday:
Frequently lifting/carrying a max of 10 lbs; rarely a max of 35 lbs
Rarely pushing/pulling a max of 20 lbs
Continuously working inside
Occasionally stooping/kneeling/crouching/crawling
Frequently sitting; occasionally standing/walking
Additional Working Conditions/Aspects:
Ability to travel between offices, as required
Ability to work flexible hours; expected to work nights and weekends as needed
Ability to work overtime, weekends, and/or holidays
Legally eligible to work in the United States
Valid driver's license (if applicable)
Must successfully complete pre-employment testing
Must be able to read and speak the English language
This job description is intended to describe the general nature, complexity, and level of work to be performed by employees assigned to this position and is not to be construed as an exhaustive list of responsibilities, duties, and/or skills required. It does not prescribe or restrict the work that may be assigned. Furthermore, this does not establish an employment contract and is subject to change at the discretion of the company.
