Product Dev Sppt Analyst III

Do you like working with data and analytics to gain insight to solve problems

Do you enjoy collaborating across teams to build and deliver products that make a difference

About Our Team

Platform Operations (Platform Ops) is a quick-growing team within Data Operations, focused on powering the next-generation Research Data Platform built on data mesh principles.

We operate at the intersection of data engineering, platform services, and supplier ecosystem management, ensuring that data products are reliable, governed, and continuously improving.

About the Role:

Data Modeling is a senior technical leader within the Data Operations function, responsible for defining and advancing structured data models, semantic frameworks, and scalable AI-enabled processing workflows.

This role sets technical standards for data modeling, Knowledge Graph development, and LLM operationalization across Data Operations. The position ensures that complex business, product, and operational requirements are translated into governed, production-ready data structures and interoperable processing pipelines.

Responsibilities:

Data Modeling Structured Content Leadership

- Define and govern logical data modeling standards across Data Operations.

- Design and maintain scalable data models supporting high-volume data processing and enrichment workflows.

- Establish canonical data principles to ensure consistency, interoperability, and governance alignment.

- Define normalization standards, transformation logic, and metadata structures for structured content ecosystems.

- Drive adoption of reusable, extensible, and future-ready modeling frameworks.

Knowledge Graph Semantic Framework Strategy

- Lead the design and evolution of semantic data models supporting Knowledge Graph initiatives.

- Define entity-relationship frameworks, ontology-aligned structures, and semantic linking strategies.

- Apply Linked Data and RDF principles to enhance contextual data relationships and interoperability.

- Provide technical leadership in integrating Knowledge Graph models within operational data workflows.

- Guide semantic enrichment strategies to improve discoverability,



entity resolution, and downstream AI applications.

Technical Specification Design Governance

- Lead comprehensive technical specification writing for complex data processing, enrichment, transformation, and semantic modeling initiatives.

- Translate business and product requirements into structured data definitions, schema designs (XSD, JSON Schema), mapping rules, and validation frameworks.

- Establish traceability between business requirements, technical specifications, and operational implementation.

- Define documentation standards and best practices for data modeling and workflow design.

Content Processing Workflow Excellence

- Architect and optimize end-to-end data and content processing workflows, including ingestion, enrichment, semantic tagging, validation, transformation, and structured output delivery.

- Define validation checkpoints, quality control mechanisms, and risk mitigation controls within operational pipelines.

- Improve operational throughput, automation maturity, and scalability.

- Establish structured testing strategies (unit, integration, regression) for complex transformations.

- Standardize workflow frameworks to enhance operational resilience and performance consistency.

Strategic Collaboration Advisory Role

- Partner with Product, Engineering, and Operations leadership to align structured data and semantic frameworks with long-term strategic objectives.

- Conduct impact assessments for new data models, workflow enhancements, enrichment initiatives, and system integrations.

- Act as the senior technical advisor for complex data, Knowledge Graph, and AI enablement initiatives.

- Influence roadmap decisions related to structured data, semantic intelligence, and automation strategy.

Qualifications Experience





- Bachelor s or Master s degree in Computer Science, Information Systems, Data Engineering, or related field.

- 8 12+ years of experience in data modeling, structured data processing, semantic modeling, or large-scale data operations environments.

- Strong expertise in content processing, enrichment workflows, metadata management, or structured data ecosystems.

- Demonstrated experience leading Knowledge Graph and semantic data modeling initiatives.

- Proven excellence in technical specification writing and workflow design governance.

- Experience operationalizing AI or LLM-driven solutions in production data environments preferred.

Requirements:

Core Data Semantic Expertise

- Advanced SQL and relational data design

- XML schema design (XSD)

- JSON schema development and transformation logic

- XML/HTML5 structured content modeling

- Knowledge Graph concepts, ontology modeling, and semantic data structures

- Data normalization, taxonomy design, and metadata governance

- Strong understanding of structured content processing techniques

Workflow Operational Systems

- End-to-end workflow architecture and process optimization

- Data validation, transformation, and quality governance frameworks

- API integration and interoperability patterns

- Data modeling and documentation tools

AI Emerging Technologies

- Strong understanding of GenAI and LLM technologies

- Experience integrating LLM-driven capabilities within structured operational workflows

- Familiarity with Retrieval-Augmented Generation (RAG) concepts

- Awareness of vector databases, embeddings, and semantic retrieval frameworks

Core Competencies

- Strategic systems-thinking and advanced problem-solving capability

- Technical authority in structured data and semantic frameworks

- Exceptional technical documentation and specification leadership

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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