Data Architect

Knowde

5d•Remote

About The Position

The Data Architect leads the design, implementation, and ongoing enrichment of product master data tailored to client needs. You'll guide Fortune 500 chemical companies through their first real data transformation—turning decades of unstructured product information into clean, governed systems that power sales, supply chain, regulatory, and customer experience. This role requires deep chemical industry expertise combined with data architecture skills. You'll run discovery sessions, establish data quality baselines, build governance frameworks, and own accuracy for client implementations. Success means customers trust their data enough to run critical business operations on it.

Requirements

Bachelor's degree in Chemistry, Chemical Engineering, Materials Science, or related technical field
3+ years of experience in the chemical industry in R&D, product development, or technical product management
Deep familiarity with chemical product data including technical data sheets (TDS), safety data sheets (SDS), formulation specifications, and regulatory documentation
Demonstrated ability to translate technical requirements into data structures and business rules
Strong communication and consultation skills with ability to educate customers on complex data architecture decisions

Nice To Haves

Advanced degree (MS or PhD) in Chemistry, Chemical Engineering, or related field
Product management experience within the chemical industry
Experience with Product Information Management (PIM) systems, Master Data Management (MDM) implementations, or data governance frameworks
Track record of successful enterprise customer implementations
Experience bridging technical R&D and commercial business functions

Responsibilities

Lead Initial Data Implementation
Guide customers through data implementation—conduct discovery sessions, document business rules, and establish data modeling best practices aligned to their primary use case
Educate customers on data architecture decisions and trade-offs
Establish baselines for data quality including accuracy and completeness post-implementation
Build Data Governance and Workflows
Develop Knowde's point of view on how client data stewardship teams should collaborate with KnowdeAI
Establish data governance models for post-implementation operations, including document collection and data management workflows
Serve as liaison between clients and internal teams to ensure integrations and ongoing maintenance align with governance standards
Own Proactive Data Maintenance and Enrichment
Maintain responsibility for accuracy and comprehensiveness of client data
Report on document gaps, data completeness, and accuracy to identify improvement opportunities
Prioritize and present actionable plans to address data gaps and enhance quality
Collaborate with Knowledge team to execute data enrichment initiatives
Enable New Use Cases
Support exploration of new use cases through customer workshops and strategic planning sessions
Assess data readiness and requirements for new use cases
Outline steps to curate and shape data to meet new requirements
Set realistic timelines and collaborate with Knowledge team on implementation
Additional Responsibilities for MDM Implementations
Own and execute data build and client data rules workstreams
Establish permanent operational data governance models and processes
Define Knowde's role in the client's document management system (DMS) strategy
Develop plans to help clients achieve target data accuracy and comprehensiveness
Identify downstream integration opportunities to enable additional use cases
Establish material mapping and taxonomy mapping to ERP systems when applicable
Additional Responsibilities for CXP Implementations
Conduct discovery and provide recommendations for custom taxonomy in Customer Experience Platform implementations