Principal Data and Semantic Architect

Parts Town•Addison, IL

5d•$129,210 - $174,374•Hybrid

About The Position

Position at Parts Town Principal Data & Semantic Architect See What We’re All About As the fastest-growing distributor of restaurant equipment, HVAC and residential appliance parts, we like to do things a little differently. First, you need to understand and demonstrate our Core Values with safety being your first priority. That’s key. But we’re also looking for unique enthusiasm, high integrity, courage to embrace change…and if you know a few jokes, that puts you on the top of our list! Do you have a genius-level knowledge of original equipment manufacturer parts? If not, no problem! We’re more interested in passionate people with fresh ideas from different backgrounds. That’s what keeps us at the top of our game. We’re proud that our workplace has been recognized for its growth and innovation on the Inc. 5000 list 15 years in a row and the Crain’s Fast 50 list ten times. We are honored to be voted by our Chicagoland team as a Chicago Tribune Top Workplace for the last four years. If you’re ready to roll up your sleeves, go above and beyond and put your ambition to work, all while having some fun, let’s chat – Apply Today! Perks Parts Town Pride – check out our 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: Access your pay as you earn it, to cover unexpected or even everyday expenses All the traditional benefits like health insurance, 401k/401k match, employee assistance programs and time away – don’t worry, we’ve got you covered. The Job at a Glance Parts Town is 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. This is a hands-on role for someone who can move between modeling, SQL, and system design, and who is comfortable stepping into the details to make sure things are built the right way.

Requirements

You have 7–10 years of experience in data engineering, analytics engineering, or data architecture in production environments.
You have deep, hands-on SQL skills and are comfortable working directly in complex warehouse environments.
You have experience working across multiple modern data warehouse platforms (e.g., BigQuery , Snowflake, Redshift, Databricks) and understand their tradeoffs.
You have strong experience modeling data using Kimball-style dimensional modeling (fact/dimension design, star schemas), and have owned or significantly influenced modeling standards.
You have built or maintained semantic layers or metrics layers that support BI and downstream applications at scale.
You have strong programming skills (Python preferred) and can build or modify APIs, services, or connectors when needed.
You have experience working closely with data engineers and are comfortable reviewing, challenging, and improving engineering implementations.
You understand how data moves across systems end-to-end, from ingestion through transformation to consumption, and have taken ownership of parts of that lifecycle.
You are comfortable operating in ambiguous environments and taking ownership of the details that make systems actually usable.
You have exposure to AI/ML or LLM-based workflows and understand how data platforms need to evolve to support them.

Responsibilities

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 overengineering.
Support AI and agent-driven use cases by ensuring data is structured, accessible, and reliable.

Benefits

Hybrid Work schedule
Team member appreciation events and recognition programs
Volunteer opportunities
Monthly IT stipend
Casual dress code
On-demand pay options: Access your pay as you earn it, to cover unexpected or even everyday expenses
All the traditional benefits like health insurance, 401k/401k match, employee assistance programs and time away – don’t worry, we’ve got you covered.
health, dental and vision insurance
401(k) with match
employee assistance programs
paid time off
paid sick time off
paid holidays
paid parental leave
professional development opportunities