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 fast-growing team within Data Operations, focused on powering the next-generation Research Data Platform built on data mesh principles.

Our team enables scalable, high-quality data services that support key Elsevier products such as Scopus, LeapSpace, SciVal, Reaxys, and other leading research solutions used globally.

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
Linked Data / RDF principles
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
Strong cross-functional influencing and advisory skills
Governance-driven mindset with operational excellence focus
Innovation-oriented with practical AI application perspective

Work in a way that works for you: -

We promote a healthy work/life balance across the organization. With an average length of service of 9 years, we are confident that we offer an appealing working prospect for our people. With numerous wellbeing initiatives, family leave and tuition reimbursement, we will help you meet your immediate responsibilities and long-term goals.

Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.

Working for you: -

At Elsevier, we know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:

Group Health Insurance Policy (covering self and family)
Group Life insurance/accident policy
Generous long-service awards
New Baby gift
Subsidized food provided (applies to India- Chennai)
Casual Leave, Sick Leave, Privilege Leave, Compassionate Leave, Special Sick Leave, Gazetted Public Holiday and Maternity/Paternity Leave
Free Transport provided to and from the office (applies to India-Chennai)

About Us: -

A global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world’s grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world.

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.

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Service Development Manager – AI Data Structuring & Readiness