Data Architect

Overview

Advan Six plays a critical role in global supply chains, innovating and delivering essential products for our customers in a wide variety of end markets and applications. Our products touch people’s lives in areas such as building and construction, fertilizers, plastics, solvents, packaging, paints, coatings, adhesives, and electronics. Advan Six delivers best-in-class customer experiences and differentiated products in the industries of nylon solutions, chemical intermediates, and plant nutrients, guided by our core values of Safety, Integrity, Accountability and Respect.

For more information, visit our website at

We offer industry-competitive benefits focused on employee well-being and a Total Rewards program that includes compensation, health, dental, vision and wellness programs, paid vacation, 401K with company matching, health savings programs, disability and life insurance, and an employee assistance program. We also provide tuition reimbursement for continued education, certifications, training, and development. You will work within a fast-paced, innovative company with passionate colleagues and partners from diverse backgrounds and experiences.

The Data Architect defines and governs the target-state architecture for Advan Six’s Unified Data Layer
, ensuring that data across SAP, OT, lab, logistics, HSE, finance, and commercial domains is structured, integrated, and modeled for scale, trust, and reuse. This role owns the architectural blueprints, canonical data models, semantic design standards, integration patterns, and data product design principles that guide engineering delivery across the enterprise. The Data Architect partners closely with the AI, Automation, and Data team to ensure that what gets built is coherent, secure, and business-ready.

• Enterprise Data Architecture

• Define and maintain the target-state architecture for the Unified Data Layer, including landing, curated, and semantic layers, domain boundaries, and consumption patterns for BI, APIs, AI, and automation.
• Develop architecture principles for modularity, interoperability, reusability, and governance across business and operational data domains.
• Serve as the design authority for major data platform and integration decisions.

• Canonical Data Modeling

• Design enterprise and domain-level canonical models for key entities such as material, product, asset, equipment, work order, batch, vendor, customer, cost center, logistics shipment, quality event, and energy usage.
• Define standards for dimensional modeling, semantic modeling, event models, and reference data structures that support Power BI, AI, and operational decision-making.
• Ensure alignment of curated and semantic data products with master data strategy and KPI canon.

• Integration and Data Product Design

• Define architectural patterns for ingesting and harmonizing data from SAP S4 HANA, SAP Data Sphere, historians, LIMS, TMS, HSE systems, and other enterprise platforms into the Unified Data Layer.
• Establish standards for data contracts, schema evolution, surrogate keys, versioning, partitioning, and semantic publication.
• Ensure that certified datasets and APIs are designed for downstream use by Reporting and BI, machine learning, Power Platform, and Copilot agents.

• Architecture Governance and Design Review

• Lead design reviews for new data products, major source integrations, and semantic layer changes.
• Approve architectural patterns and ensure alignment with security, lineage, quality, retention, and access standards.
• Partner with Data Strategy and AI Governance to operationalize architecture guardrails into delivery standards.

• Collaboration with Engineering and OT

• Work with the OT Data Integration Lead to ensure plant data models, asset hierarchies, event frames, and OT schemas fit the enterprise architecture without taking over OT connectivity operations.
• Work with Big Data Engineers to translate architecture standards into implementable pipeline, storage, and semantic design patterns.
• Partner with the Manager, Unified Data Platform and AI Engineering on platform roadmap, architecture decisions, and technical debt…