Principal Architect, Data and AI Platforms

Parts Town

Principal Architect for building a modern data and AI platform supporting analytics and AI use cases. Involves data architecture, engineering, and collaboration with teams.

Posted 5/1/2026full-timeAddison • Illinois • 🇺🇸 United StatesLead💰 $129,210 - $174,374 per yearWebsite

Tech Stack

Tools & technologies

Amazon RedshiftBigQueryPythonSQL

About the role

Key responsibilities & impact

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 for 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 for data accessibility in downstream systems and AI workflows
Build connectors or lightweight services for programmatic system interaction
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

Requirements

What you’ll need

7–10 years of experience in data engineering, analytics engineering, or data architecture in production environments
Deep, hands-on SQL skills and comfortable working directly in complex warehouse environments
Experience across multiple modern data warehouse platforms (e.g., BigQuery, Snowflake, Redshift, Databricks)
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 how data moves across systems end-to-end, from ingestion through transformation to consumption
Comfortable operating in ambiguous environments and taking ownership of detailed usability
Exposure to AI/ML or LLM-based workflows and understanding of how data platforms need to evolve to support them

Benefits

Comp & perks

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
Health insurance
401k/401k match
Employee assistance programs
Time away

ATS Keywords

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Hard Skills & Tools

SQLdimensional modelingfact/dimension designstar schemasPythonAPI developmentdata modelingdata pipeline optimizationdata transformationdata ingestion

Soft Skills

problem-solvingcollaborationownershipadaptabilitycommunicationcritical thinkingattention to detailreviewingchallenging design decisionsimproving implementations