Parts Town
Senior Director, Data and AI Platform Architect (On-site Work Schedule)
Parts Town, Chicago, Illinois, United States
Senior Director, Data and AI Platform Architect (On-site Work Schedule)
We are seeking a strategic leader to architect and scale the modern data and engineering platform that fuels Parts Town’s AI and digital ambitions. Reporting to the Global CIO, this role owns the data platform, data engineering, integration, and governance capabilities that serve as the foundation for AI-driven innovation—partnering closely with product and data science teams without directly owning those functions.
This foundational platform engineering role has a future-focused charter: build the infrastructure that unlocks real-time, reusable, and responsible data across the enterprise.
A Typical Day
Platform Architecture & Data Engineering Leadership
Lead the design and implementation of a scalable, cloud-native platform (GCP preferred) for real-time data ingestion, transformation, and serving.
Architect pipelines and semantic layers to support AI, ML, and real-time decisioning.
Modern integration patterns: API-first and event-driven architectures to unify ERP, commerce, and operational systems into a cohesive data mesh.
Data Quality, MDM & Governance
Enable trusted, governed data: partner with Data Governance to operationalize stewardship, lineage, and access controls across business domains.
Master Data Foundations: sponsor the implementation and lifecycle management of MDM platforms to ensure consistent data across customer, product, vendor, and location domains.
Support Federated Governance: create engineering capabilities (catalogs, observability, policies as code) that empower decentralized teams to operate responsibly.
Platform Enablement for AI and Digital Products
Serve as the Data Enabler for AI: deliver the infrastructure that allows AI teams to build and deploy use cases (e.g., personalization, pricing, customer service agents) efficiently and at scale.
Operationalize AI outputs: work with IT and business systems to ensure AI insights are consumable in ERP, CRM, and operational workflows.
Platform as a Product: evolve the platform with feedback to ensure high availability, low latency, and extensibility.
Strategic Leadership & Collaboration
Technology Vision & Roadmap: develop and communicate a clear roadmap for the data platform that aligns with enterprise strategy and emerging AI demands.
Cross-functional partnership: act as the connective tissue between IT, product, AI, and business units—ensuring platform capabilities align with priorities.
Support governance bodies: contribute to the Data Council and Architecture Review Board (ARB) with insight into infrastructure readiness and scalability.
Team Development
Build a high-caliber team: lead and grow a team of platform engineers, data engineers, integration specialists, and MDM experts.
Mentor & Inspire: develop engineering leadership, foster innovation, and drive a culture of continuous improvement and learning.
Drive operational excellence: implement engineering best practices in CI/CD, testing, security, and observability to maintain a reliable platform.
Qualifications
10+ years in data engineering, platform architecture, or enterprise data leadership roles.
Proven success in building modern cloud-native data platforms (GCP preferred; Azure or AWS acceptable) that support analytics and AI workloads.
Experience implementing MDM platforms and data governance tooling in a scaled enterprise environment.
Strong track record enabling AI/ML teams through high-quality, accessible data infrastructure.
Deep familiarity with ERP and operational system integrations in a B2B, e-commerce, manufacturing or distribution context.
Expert in data engineering frameworks (e.g., dbt, Airflow, Kafka, Spark) and scalable storage (e.g., BigQuery, Snowflake).
Strong grasp of API design, event streaming, and real-time data processing; familiar with AI-enabling infrastructure (e.g., vector databases, ML pipelines, feature stores).
Excellent communication skills in English (written and verbal).
Reliable high-speed internet connection at home.
About Your Future Team Our team values collaboration and innovation. We enjoy corny jokes, paintball, and Guardians of the Galaxy. We appreciate dogs and cats and a strong coffee culture. We are committed to a positive workplace where transparency, growth, and work-life balance are celebrated.
Compensation and Benefits The salary range for this role is $175,784.68 – $260,357.24, based on qualifications, experience, and geography. Parts Town is a pay-for-performance company. In addition to base pay, some roles offer a profit-sharing program and annual bonus depending on the role. Our comprehensive benefits package includes health, dental, and vision insurance, 401(k) with match, employee assistance programs, paid time off, paid sick time off, paid holidays, paid parental leave, and professional development opportunities.
Parts Town is an equal opportunity employer. We welcome diversity and all qualified applicants will be considered regardless of race, religion, color, national origin, sex, age, sexual orientation, gender identity, disability, or protected veteran status.
Seniority level Not Applicable
Employment type Full-time
Job function Engineering and Information Technology
Industries Transportation, Logistics, Supply Chain and Storage and Warehousing
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This foundational platform engineering role has a future-focused charter: build the infrastructure that unlocks real-time, reusable, and responsible data across the enterprise.
A Typical Day
Platform Architecture & Data Engineering Leadership
Lead the design and implementation of a scalable, cloud-native platform (GCP preferred) for real-time data ingestion, transformation, and serving.
Architect pipelines and semantic layers to support AI, ML, and real-time decisioning.
Modern integration patterns: API-first and event-driven architectures to unify ERP, commerce, and operational systems into a cohesive data mesh.
Data Quality, MDM & Governance
Enable trusted, governed data: partner with Data Governance to operationalize stewardship, lineage, and access controls across business domains.
Master Data Foundations: sponsor the implementation and lifecycle management of MDM platforms to ensure consistent data across customer, product, vendor, and location domains.
Support Federated Governance: create engineering capabilities (catalogs, observability, policies as code) that empower decentralized teams to operate responsibly.
Platform Enablement for AI and Digital Products
Serve as the Data Enabler for AI: deliver the infrastructure that allows AI teams to build and deploy use cases (e.g., personalization, pricing, customer service agents) efficiently and at scale.
Operationalize AI outputs: work with IT and business systems to ensure AI insights are consumable in ERP, CRM, and operational workflows.
Platform as a Product: evolve the platform with feedback to ensure high availability, low latency, and extensibility.
Strategic Leadership & Collaboration
Technology Vision & Roadmap: develop and communicate a clear roadmap for the data platform that aligns with enterprise strategy and emerging AI demands.
Cross-functional partnership: act as the connective tissue between IT, product, AI, and business units—ensuring platform capabilities align with priorities.
Support governance bodies: contribute to the Data Council and Architecture Review Board (ARB) with insight into infrastructure readiness and scalability.
Team Development
Build a high-caliber team: lead and grow a team of platform engineers, data engineers, integration specialists, and MDM experts.
Mentor & Inspire: develop engineering leadership, foster innovation, and drive a culture of continuous improvement and learning.
Drive operational excellence: implement engineering best practices in CI/CD, testing, security, and observability to maintain a reliable platform.
Qualifications
10+ years in data engineering, platform architecture, or enterprise data leadership roles.
Proven success in building modern cloud-native data platforms (GCP preferred; Azure or AWS acceptable) that support analytics and AI workloads.
Experience implementing MDM platforms and data governance tooling in a scaled enterprise environment.
Strong track record enabling AI/ML teams through high-quality, accessible data infrastructure.
Deep familiarity with ERP and operational system integrations in a B2B, e-commerce, manufacturing or distribution context.
Expert in data engineering frameworks (e.g., dbt, Airflow, Kafka, Spark) and scalable storage (e.g., BigQuery, Snowflake).
Strong grasp of API design, event streaming, and real-time data processing; familiar with AI-enabling infrastructure (e.g., vector databases, ML pipelines, feature stores).
Excellent communication skills in English (written and verbal).
Reliable high-speed internet connection at home.
About Your Future Team Our team values collaboration and innovation. We enjoy corny jokes, paintball, and Guardians of the Galaxy. We appreciate dogs and cats and a strong coffee culture. We are committed to a positive workplace where transparency, growth, and work-life balance are celebrated.
Compensation and Benefits The salary range for this role is $175,784.68 – $260,357.24, based on qualifications, experience, and geography. Parts Town is a pay-for-performance company. In addition to base pay, some roles offer a profit-sharing program and annual bonus depending on the role. Our comprehensive benefits package includes health, dental, and vision insurance, 401(k) with match, employee assistance programs, paid time off, paid sick time off, paid holidays, paid parental leave, and professional development opportunities.
Parts Town is an equal opportunity employer. We welcome diversity and all qualified applicants will be considered regardless of race, religion, color, national origin, sex, age, sexual orientation, gender identity, disability, or protected veteran status.
Seniority level Not Applicable
Employment type Full-time
Job function Engineering and Information Technology
Industries Transportation, Logistics, Supply Chain and Storage and Warehousing
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