Metadata, Discovery & Lineage Associate Director

EY is hiring a Metadata, Discovery & Lineage Associate Director within its Global Data Stewardship Office and Risk Management Data Governance discipline. The role leads the development and implementation of metadata, discovery, lineage and semantics capabilities, translating business and governance needs into supported technology solutions and measurable improvements in metadata quality, adoption and control effectiveness.

Responsibilities

• Develop and maintain the enterprise metadata, discovery, lineage and semantics capability framework, target state and implementation roadmap. Recommend specialist principles and standards for approval by the relevant owners, aligned with approved policy, risk priorities and architecture direction
• Define minimum metadata requirements by asset class, covering business, technical, operational, governance and usage metadata, and the relationships between data, processes, systems, controls, owners and permitted use context
• Design enterprise approaches for business glossaries, data dictionaries, taxonomies, semantic models, critical data elements and authoritative definitions, including governance for synonyms and justified local variation. Recommend ontologies and knowledge graphs where supported by business needs, coordinating specialist expertise for advanced implementations
• Specify risk based discovery and scanning coverage and source prioritisation; configure and validate approved connectors, APIs, harvesting schedules, indexing, search, automated classification, enrichment and exception handling across cloud and on premises environments. Evaluate platform capabilities through proofs of concept and scoped implementations, validating discovery outputs and classification results with accountable owners
• Define, configure and validate business and technical lineage, provenance and impact analysis capabilities from source to consumption, including schema, table, column, transformation, report, model and data product level traceability where proportionate to risk. Implement supported metadata and lineage ingestion patterns, reconcile platform outputs with source evidence and document coverage gaps and accountable validation
• Design, configure and test metadata lifecycle and curation controls, including metadata models, glossary and semantic relationships, approval workflows, versioning, change control, issue management, certification, deprecation and retention of history. Coordinate confirmation of owners and curators with accountable teams, and record their decisions, exceptions, escalations and auditable evidence
• Define and track metadata quality and control measures for completeness, accuracy, consistency, validity, timeliness, uniqueness, lineage and scan coverage, freshness and remediation performance. Agree measurable business outcomes with stakeholders, such as reduced time to find trusted data or assess change impacts, and use adoption and control effectiveness measures to guide improvement
• Translate approved policy and business requirements into traceable, machine-readable metadata and governance rules. Connect trusted metadata and semantic context to classifications, data quality signals, access conditions, retention, privacy, confidentiality, records, control evidence and responsible use requirements through supported integrations agreed with designated control owners
• Conduct business and user discovery with metadata consumers, Data Owners, Regional Data Stewards, Service Lines, Service Line Quality and the wider data ecosystem, including the Global Data Office (GDO), Chief Technology Officers (CTOs), Chief Information Officers (CIOs) and product and platform teams. Translate needs into business, functional and non-functional requirements, prioritised roadmaps and backlogs, user stories, supported integration patterns and measurable acceptance criteria. Agree priorities and trade-offs with relevant owners, coordinate dependencies and maintain traceability from requirements to configuration, testing and implementation evidence
• Embed governance checkpoints into design, build, release and operational handover. Execute configuration and integration testing, coordinate user acceptance testing, resolve defects and prepare release, rollback and support documentation for deployment by authorised teams. Support adoption through practical guidance and user feedback, and transition scoped capabilities to designated support owners
• Promote interoperability and vendor neutrality by applying recognised metadata registry, vocabulary, provenance and lineage patterns where appropriate, while enabling integration with enterprise catalogues and data platforms
• Facilitate definition, semantic modelling and lineage validation workshops with business, Service Line Quality, data and technology stakeholders. Explain technical concepts in practical business language, negotiate priorities, resolve cross-domain dependencies and build agreement on delivery, adoption and outcomes. Recommend options and escalate unresolved conflicts to the relevant decision owners
• Monitor relevant industry practices, standards, regulatory developments and technology capabilities, and direct continuous improvement of the metadata and lineage operating model

Skills

• Bachelor's degree or equivalent tertiary qualification in information systems, computer science, software or data engineering, data science, data architecture or a related discipline, or equivalent substantial professional experience in technology implementation. Candidates from information management, library or information science, business or other disciplines are welcome where they demonstrate equivalent technical foundations, practical implementation capability and relevant metadata management, information architecture and data governance knowledge
• 8 or more years of relevant experience, including substantial responsibility for enterprise metadata, data catalogues, automated discovery and classification, lineage, semantic or information architecture capability in a complex organisation
• Demonstrated success defining metadata models and standards and implementing harvesting and enrichment across multiple platforms. Hands-on implementation experience with at least one enterprise metadata catalogue or data governance platform is essential, including configuring metadata models, discovery or classification capabilities, curation workflows and supported integrations with cloud data platforms, APIs or automation tools. Candidates must demonstrate delivered configurations, validated outputs and implementation evidence alongside requirements or advisory expertise
• Experience establishing business glossaries, taxonomies or ontologies and improving enterprise search and data discoverability, including configuring semantic relationships, accountable curation and approval workflows in enterprise tools
• Experience delivering and validating business and technical lineage, provenance and impact analysis through supported connectors, APIs or lineage event patterns, and implementing curation, metadata quality rules and remediation processes. Demonstrated use of SQL and scripting to reconcile source evidence, metadata and lineage outputs
• Demonstrated experience applying product management practices to metadata, discovery, lineage or semantics delivery: discovering business and user needs, defining business, functional and non-functional requirements, developing roadmaps and prioritised backlogs, and managing dependencies and trade-offs with product and platform teams. Experience supporting design, hands-on configuration or integration, testing, approved release, adoption and operational handover, with measurable acceptance criteria and evidence of business value and control outcomes
• Evidence of measurable improvements from technology-enabled governance, such as increased discovery and classification coverage, more complete or reliable lineage, improved metadata quality and freshness, faster curation, automated control evidence or greater use of trusted definitions and governed data
• Experience influencing senior stakeholders outside the reporting line in a global matrix, engaging business, Service Lines, Service Line Quality and data and technology teams, and working with architecture, product, engineering, analytics, AI, privacy, security and records functions. Evidence of facilitating decisions, negotiating priorities and building agreement on delivery and adoption across organisational boundaries
• Deep expertise in metadata management across business, technical, operational, governance and usage metadata, including catalogues, metadata repositories, data dictionaries and metadata lifecycle controls
• Advanced knowledge of automated data discovery, profiling, scanning, indexing, classification, connector and API patterns, enrichment, search relevance and coverage management across hybrid data estates
• Advanced knowledge of business and technical lineage, provenance, transformation logic, dependency mapping and impact analysis, including practical approaches to table, column, report, model and data product level traceability
• Strong capability in business glossaries, controlled vocabularies, taxonomies and semantic relationships, including governance of authoritative definitions and synonyms. Working understanding of ontologies and knowledge graphs and when they add value
• Ability to apply relevant recognised practices pragmatically: DAMA-DMBOK for metadata management, governance and data quality; EDM Association (formerly EDM Council) DCAM for capability assessment and improvement; and CDMC for cloud data management and automated control evidence where applicable
• Practical understanding of governance controls that connect metadata to data quality, confidentiality, privacy, security, records, retention, access, permitted use, analytics and responsible AI
• Hands-on skills in enterprise metadata catalogue or governance platform configuration, including metadata modelling, discovery and classification rules, glossary and semantic relationships, lineage ingestion, metadata quality rules and curation workflows. Ability to assess capability fit, implement supported API, connector or scripting-based integrations and validate results. Practical delivery capability in a relevant platform is essential; expertise in every platform, graph technology or observability tool is not required
• Practical understanding of cloud data platforms, APIs, pipelines and interoperability. Ability to use SQL and an appropriate scripting language, such as Python, to inspect schemas, validate harvested metadata and transformation logic, reconcile lineage and test metadata quality and supported integrations
• Ability to define metadata and lineage quality rules, control evidence, service measures and outcome metrics, and to use those measures to prioritise remediation and continuous improvement
• Strong knowledge of product management practices appropriate to specialist capability delivery: business and user discovery, roadmaps, backlog prioritisation, agile delivery, dependency and trade-off management, testing, approved release, adoption and value measurement. Ability to translate business needs into business, functional and non-functional requirements, user stories, technical specifications, metadata schemas, machine-readable rules, workflows and measurable acceptance criteria, with traceability to delivery and control evidence
• Working knowledge of version control, environment separation, configuration and integration testing, defect management, approved deployment and rollback, least-privilege access and secure handling of credentials. Ability to document metadata models, connectors, rules and workflows and transition scoped capabilities to designated support owners
• Strong analytical, facilitation, communication, relationship-building and negotiation skills. Ability to explain technical concepts in practical business language, translate business needs into implementable solutions and influence stakeholders outside the reporting line, including business, Service Line Quality, governance, data, risk and technology communities
• Ability to build agreement on pragmatic enterprise standards, delivery priorities, adoption and outcomes in a global, federated organisation while accommodating justified legal, regulatory, regional and business variation and respecting accountable owners' decisions
• Advanced implementation expertise in these areas is advantageous rather than essential
• Familiarity with relevant interoperability standards, such as ISO/IEC 11179 metadata registries, ISO 8000 data quality, W3C DCAT, SKOS and PROV, or OpenLineage event patterns, is advantageous
• Familiarity with lakehouse, data mesh or data fabric approaches is advantageous where relevant to the implementation environment
• Practical experience implementing relevant metadata, discovery, classification or lineage capabilities through Microsoft Purview, Databricks Unity Catalog or Microsoft Fabric/OneLake is advantageous. Comparable experience with platforms such as Collibra, Informatica IDMC, Alation, Atlan or DataHub is also valued. Experience should demonstrate applied configuration and integration relevant to this role; experience with every named platform is not required
• Experience in a federated professional services, financial services or comparably regulated global environment is advantageous
• Relevant credentials such as DAMA Certified Data Management Professional, EDM Association DCAM or CDMC, information architecture, knowledge graph, technology product management, cloud data platform, metadata catalogue or data governance platform certifications are advantageous but not mandatory

Benefits

• Medical and dental coverage
• Pension and 401(k) plans
• A wide range of paid time off options
• Flexible vacation policy
• Time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.

Company Overview

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