Principal Data and Semantic Architect; Hybrid

Principal Data & Semantic Architect, Parts Town

We are building a modern data and AI platform to support advanced analytics and emerging AI use cases across a rapidly growing organization. As an AI Platform Engineer, you will operate at the intersection of data architecture and hands‑on engineering, helping shape how data is modeled, exposed, and used across the business.

This role focuses on owning and improving the core data foundations that power analytics and AI, from warehouse design and dimensional modeling to semantic layer development and system integration. You will work directly in the code and data, defining practical standards, reviewing implementations, and ensuring consistency and quality across the platform.

You will partner closely with data engineers to challenge and refine solutions, ensuring the platform is built for scalability, usability, and reuse. You will also collaborate with product, governance, and security stakeholders to align on definitions, data quality, and access patterns so that data can be trusted and consistently used across the organization.

• Design and refine dimensional data models (fact/dimension, star schemas) to support analytics and AI use cases.
• Write, review, and optimize SQL used across the warehouse and semantic layer.
• Build and evolve the semantic or metrics layer to ensure consistent, trusted business definitions.
• Partner directly with data engineers to review implementations, challenge design decisions, and improve data pipelines.
• Debug data issues across the stack, from ingestion through transformation to consumption.
• Modify or extend APIs and services to make data and functionality accessible for downstream systems and AI workflows.
• Build connectors or lightweight services that enable systems to interact programmatically.
• Translate business and product requirements into practical data models and system designs.
• Identify gaps in the current architecture and drive pragmatic improvements without over engineering.
• Support AI and agent‑driven use cases by ensuring data is structured, accessible, and reliable.

• 7–10 years of experience in data engineering, analytics engineering, or data architecture in production environments.
• Deep, hands‑on SQL skills and comfort working directly in complex warehouse environments.
• Experience across multiple modern data warehouse platforms (e.g., Big Query, Snowflake, Redshift, Databricks) and understanding their trade‑offs.
• Strong experience modeling data using Kimball‑style dimensional modeling (fact/dimension design, star schemas).
• Built or maintained semantic layers or metrics layers that support BI and downstream applications at scale.
• Strong programming skills (Python preferred) and ability to build or modify APIs, services, or connectors when needed.
• Experience working closely with data engineers and comfortable reviewing, challenging, and improving engineering implementations.
• Understanding of end‑to‑end data flow from ingestion through transformation to consumption.
• Comfort operating in ambiguous environments and taking ownership of details that make systems usable.
• Exposure to AI/ML or LLM‑based workflows and understanding how data platforms need to evolve to support them.

• Parts Town Pride – virtual tour and culture.
• Hybrid work schedule.
• Team member appreciation events and recognition programs.
• Volunteer opportunities.
• Monthly IT stipend.
• Casual dress code.
• On‑demand pay options.
• Health, dental, and vision insurance.
• 401(k) with match.
• Employee assistance programs.
• Paid time off, sick time off, paid holidays, paid parental leave.
• Professional development opportunities.

Salary range: $ – $ (based on qualifications, experience, and location). Parts Town is a pay‑for‑performance company, offering profit sharing and annual bonuses for certain roles.

Parts Town welcomes diversity and, as an equal‑opportunity employer, all qualified applicants will be considered regardless of race, religion, color, national origin, sex, age, sexual orientation, gender identity, disability, or protected veteran status.