Knowledge Graph Architect Jobs (NOW HIRING)

We are building an intelligence layer for the distributed energy industry.

Across our businesses, we operate in solar, battery storage, energy distribution, software, financing, installation workflows, after-sales services and energy assets. Together, these businesses generate significant operational data across customers, installers, suppliers, products, proposals, orders, projects, physical assets, financing and post-installation performance.

Our next challenge is not simply to centralise this data. It is to create a common digital representation of the distributed energy ecosystem: a shared Energy Ontology that enables our software, analytics systems and AI agents to understand how the real world is structured, how entities relate to one another, how they change over time and what actions can be taken.

We are looking for a Principal Knowledge Architect to lead this effort.

This is a rare opportunity to design a knowledge architecture from the ground up across a global, multi-business energy platform. You will have the opportunity to define the foundational model that shapes how data, software and AI operate across the group.

This is not a traditional Data Engineer, BI, Data Warehouse or Enterprise Architecture role. You will define the semantic and knowledge architecture that sits between our underlying data infrastructure and the AI applications, decision systems and operational workflows built on top of it.

Define and continuously evolve the canonical ontology for the distributed energy ecosystem.

You will establish:

• Core business objects and entity definitions
• Attributes, properties and relationships
• Events, states and lifecycle transitions
• Actions and business rules
• Identifiers and source-of-truth principles
• Provenance and data lineage
• Temporal and geospatial relationships

You will ensure that different businesses and systems describe the same real-world entities consistently.

Work across multiple platforms and data sources to establish a shared representation of customers, installers, products, orders, projects, properties and energy assets.

• Which systems and sources are authoritative
• How entities are identified across platforms
• How duplicate entities should be resolved
• How information can be appropriately shared across businesses
• How entities and relationships evolve over time
• How common models can be used across software products without requiring every application to share the same physical database

You will work closely with our global data and platform engineering teams, including our China-based Data Platform Team.

The Principal Knowledge Architect will own the ontology, semantic architecture, canonical object definitions, relationship models, knowledge architecture, data contracts, ontology governance, knowledge graph architecture and AI readiness of enterprise data.

Our Data Platform Team owns ingestion, pipelines, storage, transformation, APIs, infrastructure, data quality implementation, platform engineering and production systems.

Together, you will translate complex business reality into scalable production data infrastructure.

Design the knowledge foundation that enables future AI systems to understand entities, relationships, state and operational context.

This could enable AI systems to understand:

• Who a customer is across multiple interactions and businesses
• Which installer services a customer or property
• Which energy assets and products exist at a property
• Which products and systems are compatible
• Which proposals are most likely to convert
• Which financing options may be appropriate
• What has happened previously and what state an entity is currently in
• What action a system should take next

The goal is to make enterprise data understandable and actionable for intelligent applications, not simply accessible.

Develop the architecture required to connect fragmented records representing the same real-world entities.

This may include installers represented differently across multiple systems, customers interacting across different businesses, products appearing under different distributor SKUs, and installations connected to properties, products, installers, financing and performance records.

You will define approaches for:

• Entity resolution and identity matching
• Knowledge graph construction
• Confidence scoring
• Source-of-truth management
• Data lineage and provenance

Ensure the Energy Ontology remains a governed, reusable enterprise capability rather than becoming another uncontrolled schema.

• Creating and modifying objects
• Versioning and backwards compatibility
• Ownership and permissions
• Naming conventions
• Documentation
• Ontology review and approval

You will ensure the ontology remains reusable across businesses and is not optimised for one application at the expense of the wider platform.

You will bring 8+ years of relevant experience across knowledge architecture, semantic data modelling, data architecture, data platforms or related disciplines.

We are particularly interested in candidates with meaningful experience across several of the following areas:

• Knowledge graphs
• Canonical enterprise data models
• Entity resolution and identity matching
• Product or customer knowledge graphs
• Master Data Management
• Metadata and taxonomy systems
• Data contracts and governance
• AI knowledge systems

You should be comfortable working across both technical and business domains and be able to translate complex real-world concepts into scalable data and knowledge structures.

You should have a strong understanding of:

• SQL and Python
• APIs
• Relational and graph databases
• Event-driven architectures
• Data lineage and quality
• Identity and entity resolution

Experience with technologies such as Neo4j, RDF, OWL, SPARQL, GraphQL, Kafka, Snowflake, Databricks, or equivalent technologies is valuable but not mandatory.

We care more about your ability to design the right conceptual and knowledge architecture than your attachment to any specific technology.

You may have worked in complex, data-rich platform environments involving large-scale knowledge, identity, marketplace, workflow, data or operational intelligence systems.

Experience in environments similar in complexity to Palantir, Amazon, Google, Microsoft, Salesforce, ServiceNow, Uber or Airbnb may be particularly relevant, but we are equally interested in candidates from other organisations who have solved comparable problems at significant scale.

What matters is your ability to create shared models of real-world entities, connect fragmented systems and make enterprise data usable for intelligent applications and operational decision-making.

This is not primarily a:

• Dashboard or BI role
• Data warehouse or ETL role
• LLM prompt engineering or chatbot role
• ERP implementation role
• Pure research ontology role

We are looking for someone who can connect business reality, ontology, data, AI, decisions and actions and translate that architecture into practical systems used across a growing global business.

If you are excited by the challenge of creating the knowledge foundation that allows data, software and AI to understand and act on the distributed energy ecosystem, we would like to hear from you.