Data Architect (IRC306922)

Job Description

Candidate evidence

Candidates should be prepared to present a sanitised example of work they personally led or substantially

contributed to, such as an enterprise conceptual model, business or domain ontology, taxonomy or cross-system

semantic harmonisation initiative. Experience limited to physical schemas, dimensional models or ERDs derived

from source systems is not sufficient.

Must-have experience

Demonstrable hands-on delivery of conceptual data models in complex enterprise environments.

Practical experience developing or applying business or domain ontologies, taxonomies or related knowledge-representation models.

Experience defining concepts independently of application schemas and vendor technologies.

Experience reconciling conflicting terminology and entity representations across systems or business

domains.

Strong understanding of identity, classification, relationships, cardinality, grain, time, lifecycle and business

rules.

Proven ability to facilitate decisions with business experts and architecture stakeholders and communicate clearly in English.

Ability to translate conceptual work into logical models and practical implementation guidance.

Nice-to-have experience

Energy, utilities, industrial infrastructure, asset management or service domains.

Modelling assets, equipment, telemetry, maintenance, documents, media evidence or AI-generated

observations.

Metadata management, business glossaries, lineage, provenance and data governance.

Knowledge graphs or standards such as RDF, RDFS, OWL, SKOS or SHACL.

Dimensional modelling, Data Vault, modern lakehouse patterns and open semantic specifications such as

Apache Ossie.

Awareness of Microsoft Azure, Fabric, Databricks, dbt and multi-region or multi-tenant data platforms.

Job Responsibilities

Key responsibilities

Work with business experts and architects to define important concepts, terminology, classifications and

relationships.

Develop and maintain enterprise and domain conceptual data models, taxonomies and pragmatic business

ontologies.

Distinguish business concepts from source-system records, application objects, tables and APIs.

Reconcile conflicting terminology, identifiers and representations across SAP, Salesforce, IoT and other

systems.

Define entity identity, lifecycle, temporal meaning and relationships, including evidence, observations and

machine-derived assertions.

Translate conceptual models into logical models, data contracts and implementation guidance together with

data architects and engineers.

Maintain traceability from business definitions to source data and downstream data products.

Facilitate modelling workshops, document semantic decisions and establish practical modelling standards.

Expected deliverables

Enterprise and domain conceptual data models

Governed vocabulary, definitions and synonyms

Taxonomies, classification models and a pragmatic business or domain ontology

Entity identity, relationship, lifecycle and temporal definitions

Concept-to-source and concept-to-logical-model mappings

Modelling standards, semantic decision records and implementation guidance

Department/Project Description

Project context

The project is a long-term data platform initiative for the energy infrastructure domain. It will

integrate enterprise data from SAP, Salesforce and legacy systems with IoT telemetry, documents, images and

machine-derived observations. The platform will support analytics, applications and governed AI use cases

across multiple regions, tenants and cloud environments.

Role purpose

Lead the development of the enterprise conceptual data model and supporting ontology. Establish consistent

business meaning across domains and source systems, then guide its translation into logical models, data

products and semantic definitions.