Data Enterprise Architect

Pontoon Solutions; Warwick; Presencial; GBP 90.000 - 130.000; Jornada completa

Descripción de la vacante

Pontoon Solutions in the United Kingdom is seeking a Senior Data Enterprise Architect to define and evolve our data landscape. You will map current architectures, model domains, and work with transformation teams to improve data assets and enable informed decision making.

You will establish enterprise information models, data domains, and governance patterns, partnering with business and tech teams to ensure data is trusted, reusable and AI-ready across programmes.

Formación

• Evidence of leadership in enterprise data architecture within complex organisations.
• Strong ability to model data at conceptual and logical levels with domain focus.
• Experience building semantic models, glossaries and knowledge structures.
• Expertise in metadata, data lineage, data quality and governance.
• Familiarity with TOGAF, DAMA DMBoK or equivalent frameworks.

Responsabilidades

• Develop and evolve enterprise data architecture, standards and information models.
• Define data domains, business concepts and key relationships across systems.
• Set metadata, lineage, master data patterns and interoperability standards.
• Define architectural foundations for data products and federated operating models.
• Collaborate with architecture, engineering and business teams to align with data principles.
• Provide leadership and assurance into projects and governance processes.
• Support semantic models and knowledge structures to enable AI-enabled services.

Conocimientos

Data architecture

Data modelling

Stakeholder engagement

Semantic models

Metadata management

Data governance

Data lineage

APIs & data services

TOGAF

Herramientas

ArchiMate

UML

ERD

BizzDesign

Sparx EA

Azure / Fabric / PowerBI

Databricks

Snowflake

Informatica

MuleSoft

Descripción del empleo

In short:

We’re seeking a strong, senior Data Enterprise Architect to define the data landscape across our business. This is not an ivory tower role. The perfect person would be able to map out and assess the current state of data architecture, work with transformation teams to improve areas while modelling the conceptual and logical piece. You need to have the skills to dig deep where possible and confidently present findings that will be used for decision-making. A hands-on, consultative approach is what we need.

In full:

Role overview:

Establish and evolve the data domain of the enterprise architecture to ensure data is trusted, connected, reusable and ready to support business decisions, regulatory obligations, data products and AI-enabled services.

The role will define the enterprise information models, data domains, architectural principles, semantic models and knowledge structures that help manage data as a strategic asset. Working across business and technology teams, the role will ensure information can be consistently understood, governed, shared and reused whilst supporting a federated model of ownership and accountability.

Key accountabilities:

• Develop, maintain and evolve the enterprise data architecture, including architectural principles, standards, information models and current/transitional/target-state designs that support consistent, trusted and reusable data.
• Define and maintain enterprise information models, data domains, business concepts and key data relationships, ensuring critical information is consistently understood and managed across systems, processes and business areas.
• Establish architectural standards and patterns for metadata, lineage, master data, reference data and interoperability, enabling data to be discovered, understood, governed and reused.
• Define the architectural foundations needed to support data products and the necessary operating model (e.g. federated / hybrid), ensuring data can be shared, consumed and reused consistently across business domains and analytical use cases.
• Work with architecture, engineering and business teams to ensure new solutions align with agreed data principles, information standards and long-term enterprise objectives.
• Provide data architecture leadership and assurance into portfolios, projects, programmes and governance processes, identifying opportunities to improve reuse, reduce duplication and strengthen information quality and consistency.
• Support the development of semantic models, business glossaries and knowledge structures that improve understanding of enterprise information and support AI-enabled services.
• Work with Data Owners, Data Stewards and delivery teams to ensure ownership, governance, quality and lifecycle considerations embedded into solution design and implementation.
• Promote enterprise thinking, helping business areas balance local requirements with wider organisational value, reuse and interoperability.
• Monitor and improve the maturity of enterprise data architecture capabilities, identifying opportunities to strengthen information management, data sharing, governance and AI readiness.

Essential knowledge / experience:

• Significant experience in enterprise data architecture, information architecture or data leadership roles within a complex organisation.
• Strong data modelling expertise across conceptual, logical and (to a lesser extent) physical data models, including enterprise information and domain modelling.
• Strong stakeholder engagement and influencing skills, with the ability to communicate complex concepts to technical and non-technical audiences
• Experience developing semantic models, ontologies, taxonomies, business glossaries or knowledge structures.
• Strong knowledge of metadata, data lineage, data quality, master data management and data governance.
• Experience defining enterprise architecture principles, standards and target architectures.
• Practical understanding of different data architecture paradigms and styles, including Data Warehouse, Data Lake, Data Lakehouse, etc.
• Understanding of Data Mesh concepts and federated approaches to data ownership and reuse.
• Experience with integration, interoperability, APIs and reusable data services.
• Experience using recognised architecture methods and tools such as ArchiMate, UML, ERD, BizzDesign (preferred), Sparx EA or equivalent.
• Practical architect experience and ongoing learning of multiple enterprise data, analytics, integration and AI architectures and technology solutions, their differences, pros and cons (e.g. Ms Azure / Fabric / PowerBI, Databricks, Snowflake, Informatica, MuleSoft).
• Knowledge of recognised frameworks such as TOGAF, DAMA DMBoK or equivalent industry practice.

Candidates will ideally show evidence of the above in their CV in order to be considered.

Please be advised if you haven't heard from us within 48 hours then unfortunately your application has not been successful on this occasion, we may however keep your details on file for any suitable future vacancies and contact you accordingly. Pontoon is an employment consultancy and operates as an equal opportunities employer.

We use generative AI tools to support our candidate screening process. This helps us ensure a fair, consistent, and efficient experience for all applicants. Rest assured, all final decisions are made by our hiring team, and your application will be reviewed with care and attention.