Key Responsibilities and Required Skills for Information Planner

🎯 Role Definition

The Information Planner is a cross-functional professional who designs and operationalizes enterprise information architecture, metadata schemas, taxonomy and classification systems, and content lifecycles to improve findability, governance, compliance, and business value. This role partners with product managers, data engineers, knowledge managers, legal/compliance, and business stakeholders to translate organizational information needs into practical information models, tagging strategies, standards, and implementation roadmaps that drive measurable search, discovery and analytics outcomes.

📈 Career Progression

Typical Career Path

Entry Point From:

Information Analyst / Knowledge Analyst
Business Analyst with data or taxonomy emphasis
Records Manager, Librarian, or Content Strategist

Advancement To:

Information Architect / Lead Information Planner
Head of Information Governance or Knowledge Management
Director of Data Management or Chief Data Officer

Lateral Moves:

Data Governance Manager
Content Strategy Lead
Enterprise Search Manager

Core Responsibilities

Primary Functions

Develop and maintain enterprise information architecture and taxonomy frameworks that support search relevance, content discoverability, and cross-channel consistency, ensuring alignment with business goals and user needs.
Design, document and operationalize metadata models and controlled vocabularies (including naming conventions, attributes, hierarchies and synonyms) that improve indexing, personalization, and analytics across content and data platforms.
Lead the creation and rollout of classification and tagging strategies for structured and unstructured content, defining tagging rules, automated enrichment patterns, manual curation guidelines and validation checks.
Collaborate with data engineering and product teams to scope and specify metadata ingestion pipelines, data catalog integrations, API contracts and mapping rules that ensure consistent lineage and provenance.
Define and enforce information governance policies—retention, access controls, legal holds, PII handling, and data stewardship responsibilities—working with legal, compliance, and security stakeholders to meet GDPR/CCPA and industry-specific requirements.
Conduct stakeholder discovery sessions and requirements workshops to translate business use cases into concrete information models, KPIs, and prioritized roadmaps that balance effort, impact, and risk.
Build and maintain a business glossary and master metadata repository (MMR) that documents definitions, ownership, usage examples, and relationships for critical business entities and content types.
Implement and govern taxonomy versioning, change management, and approval workflows, including RACI matrices, release notes and communication plans for taxonomy updates and migrations.
Partner with search engineers and UX designers to optimize search schemas, facets, ranking signals, and result grouping, and to measure improvements in query success, click-through and time-to-answer.
Design and run metadata quality programs—rule-based validation, sampling, anomaly detection and remediation processes—to improve completeness, accuracy and consistency of information assets.
Author clear documentation, standards and onboarding materials (style guides, metadata playbooks, QA checklists) to enable content producers, developers and data stewards to follow consistent practices.
Translate business taxonomies and ontologies into machine-readable formats (JSON-LD, RDF, SKOS, OWL) and coordinate implementation for semantic search, knowledge graphs and AI/LLM-enhanced applications.
Manage vendor relationships and third-party tools for taxonomy management, data cataloging and search (e.g., Alation, Collibra, PoolParty, Elasticsearch, Coveo), including requirements, procurement support and implementation oversight.
Create dashboards and measurement frameworks to monitor taxonomy adoption, metadata coverage, search performance, information access metrics and business outcomes tied to content discoverability.
Lead pilot projects and phased rollouts to implement taxonomy and metadata changes with minimal disruption, iterating based on user feedback and usage analytics.
Facilitate cross-functional data stewardship councils and working groups to arbitrate taxonomy decisions, prioritize tag maintenance, and resolve conflicts between business domains.
Provide technical specifications and acceptance criteria for engineering teams to implement metadata APIs, ETL transformations, indexing pipelines and content migration scripts.
Assess and recommend tooling, automation and enrichment strategies (NLP tagging, entity extraction, ML-assisted taxonomy suggestions) to scale metadata capture and reduce manual effort.
Coordinate information lifecycle management (ILM) initiatives—archiving, retention schedules, disposal and legal hold processes—to reduce risk and storage costs.
Design role-based access and entitlements for sensitive content and metadata, ensuring compliance with least-privilege principles and audit requirements.
Run training, change management and evangelism programs to raise organizational metadata literacy, champion best practices, and accelerate adoption of new taxonomies and tools.
Lead post-implementation reviews and continuous improvement cycles to refine taxonomy structures, governance processes and tooling based on operational metrics and stakeholder feedback.
Support roadmap planning by estimating effort, tracking dependencies, and integrating taxonomy and metadata initiatives into broader product and data roadmaps.
Coordinate content migrations and taxonomy remaps during platform consolidations, acquisitions or CMS upgrades, planning cutover strategies and rollback contingencies.

Secondary Functions

Support ad-hoc data requests and exploratory data analysis.
Contribute to the organization's data strategy and roadmap.
Collaborate with business units to translate data needs into engineering requirements.
Participate in sprint planning and agile ceremonies within the data engineering team.
Assist in vendor evaluations, POC testing and implementation validation for knowledge management and search tools.
Provide subject-matter expertise during compliance audits and information governance assessments.

Required Skills & Competencies

Hard Skills (Technical)

Information architecture and taxonomy design, including hierarchical and faceted classification models.
Metadata modeling and management (business glossary, data catalog concepts, attribute design).
Familiarity with metadata and semantic standards: RDF, SKOS, OWL, JSON-LD, Dublin Core.
Experience with search platforms and tuning (Elasticsearch, Solr, Coveo, Algolia) and knowledge of ranking, facets and relevancy tuning.
Hands-on experience with data catalog and governance tools (e.g., Alation, Collibra, Informatica, PoolParty) or comparable systems.
Knowledge of content management systems and enterprise platforms (SharePoint, Drupal, AEM, Confluence) and how metadata integrates with them.
Basic to intermediate SQL for metadata and content queries; familiarity with data pipelines / ETL concepts.
Experience with analytics and dashboarding tools (Tableau, Power BI, Looker) to monitor taxonomy metrics and adoption.
Familiarity with NLP/ML techniques for automated tagging, entity extraction and semantic enrichment; experience with Python or scripting for prototyping is a plus.
Understanding of data governance frameworks, retention policies, privacy and compliance standards (GDPR, CCPA, ISO 27001).
API specification and integration knowledge (REST, GraphQL) to support metadata exchange and automation.
Experience converting taxonomies into machine-readable ontologies and integrating knowledge graphs.
Change management and rollout planning for taxonomy and CMS migrations.

Soft Skills

Strong stakeholder management and facilitation skills to align diverse business units on taxonomy decisions.
Excellent written communication and documentation skills to produce clear metadata standards, playbooks and governance artifacts.
Analytical mindset with ability to define and measure KPIs, diagnose metadata issues and propose data-driven solutions.
Project management and prioritization skills; ability to coordinate cross-functional releases and manage timelines.
Problem-solving orientation and ability to work in ambiguous, multi-stakeholder environments.
Training and coaching skills — able to run workshops and drive adoption across large user populations.
Collaborative team player with empathy for content creators, engineers and compliance partners.
Attention to detail and focus on quality assurance for metadata and classification tasks.
Adaptability to new tools and emerging semantic technologies.

Education & Experience

Educational Background

Minimum Education:

Bachelor's degree in Information Science, Library & Information Studies, Computer Science, Business, or related field.

Preferred Education:

Master's degree (MLIS, Information Science, Knowledge Management, Data Management) or relevant professional certifications (e.g., Certified Information Professional, Data Governance certificates).

Relevant Fields of Study:

Information Science / Library Science
Knowledge Management
Computer Science / Information Systems
Business Analytics / Data Management
Linguistics or Cognitive Science (for taxonomy/NLP focus)

Experience Requirements

Typical Experience Range: 3–7 years of progressive experience in information architecture, taxonomy, metadata management, content strategy, or related data roles.

Preferred: 5+ years in enterprise environments with cross-functional governance responsibilities, demonstrated success implementing taxonomy programs, data catalog integrations, or search optimization projects. Proven track record of stakeholder facilitation, documentation, and measurable improvements in discoverability or compliance outcomes.