Service Development Manager - AI Data Structuring & Readiness

relx

Chennai District

On-site

INR 3,000,000 - 5,200,000

Full time

2 days ago
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Job summary

RELX is seeking a senior Data Modeling expert to lead structured data and semantic frameworks within Platform Operations. You will shape data models, governance, and semantic strategies across Data Operations, collaborating with product and engineering teams to advance AI-enabled processing workflows.

The role emphasizes Knowledge Graph design, semantic enrichment, and scalable data pipelines, with experience in production AI or LLM-driven solutions preferred.

Qualifications

  • 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 ops 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.

Responsibilities

  • Lead data modeling and governed structured data standards across Data Operations.
  • Design and maintain scalable data models supporting high-volume processing and enrichment workflows.
  • Define normalization standards, transformation logic, and metadata structures for structured content ecosystems.
  • Drive adoption of reusable, future-ready modeling frameworks.
  • Lead Knowledge Graph and semantic data modeling initiatives and alignment with AI enablement.

Skills

Advanced SQL
Relational data design
Knowledge Graph
Semantic data modeling
LLM enablement

Education

Bachelor's or Master's in CS/IS/Data Eng

Tools

XML schema design (XSD)
JSON Schema development
XML/HTML5 structured content modeling
Linked Data / RDF

Job description

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

  • Knowle

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