Analytics Architect

Rumpke Careers•Cincinnati, OH

About The Position

The Analytics Architect is part of the Data and Analytics team and works between data engineering and the business, turning raw, well-structured data into governed, business-friendly semantic models used by self-service tools and analysts. The role owns semantic layer strategy and architecture across all business domains, 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 in architectural thinking. The position does not manage employees.

Requirements

Bachelor's degree in Computer Science, Analytics, or a related field.
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 a comparable cloud data warehouse architecture, semantic layers, and SQL.
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.
Ability to travel between offices, as required.
Ability to work flexible hours and 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 English.

Nice To Haves

Master's degree.
dbt Analytics Engineering Certification.
Snowflake SnowPro Core Certification.

Responsibilities

Define and own 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 and analytics layer, weighing cost, scalability, and long-term maintainability.
Identify cross-domain architectural risks or inconsistencies and drive resolution across multiple domains.
Partner with the Data Architect to align platform architecture with analytics and semantic layer architecture.
Advise team leadership on long-term analytics architecture strategy, including the effects of current decisions on 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.