Data & Platform Architect

Own the target architecture for Falkor’s shared data, knowledge and platform services. You will help ensure that products, integrations and AI-enabled experiences are built on secure, scalable, resilient and governed foundations.

About Falkor

Falkor is a KONGSBERG company helping organisations in heavy-asset industries improve how assets are designed, operated and optimised across their lifecycle. Our industrial intelligence platform connects people, systems, data and workflows, turning complexity into clarity and data into decisions.

The role

As Data & Platform Architect, you will define and evolve the architecture for shared platform capabilities spanning data ingestion, processing, storage, eventing, APIs, metadata, search, knowledge graphs and workflow orchestration. You will set clear architectural direction, establish reusable patterns and work with product and engineering teams to translate business needs into sustainable platform decisions.

This is a senior individual-contributor role with broad influence across product and engineering. It is suited to an architect who can combine strategic direction with practical technical guidance.

What you will do

Platform and data architecture

Define and maintain the target architecture and transition roadmap for shared data, knowledge and platform services.

Establish reusable patterns for data ingestion, processing, storage, event streaming, APIs, integration and workflow orchestration.

Guide architectural decisions across relational, document, time-series, graph, vector and unstructured data systems.

Drive cloud-native, event-driven and API-first practices, while balancing scalability, resilience, security and cost.

Ontology, knowledge and search

Define and govern enterprise ontologies, semantic models and knowledge graph architectures that connect industrial assets, systems, documents, workflows and operational data.

Establish standards for taxonomy, metadata, lineage, semantic interoperability and the lifecycle of knowledge assets.

Shape architectures for enterprise search, semantic discovery, contextual retrieval and AI‑ready knowledge services.

Enable a unified intelligence layer that connects trusted data, knowledge, search and workflows to support discovery, traceability, decision support and AI-powered experiences.

Governance and operational quality

Establish architecture principles, standards and lifecycle controls for platform services, data pipelines and knowledge assets.

Ensure cross-cutting requirements for security, access control, observability, reliability, performance and cost optimisation are designed into the platform.

Promote interoperability across platform modules, applications, AI services and external integrations.

Create pragmatic decision records and reference architectures that make standards easy for teams to adopt.

Technical leadership and collaboration

Partner with Product Managers, Application Architects, Infrastructure Architects and Engineering teams to align platform investments with business priorities.

Provide hands‑on technical guidance for data platforms, messaging, search, graph technologies, workflow engines, APIs and high‑performance data access.

Mentor engineers and architects in data engineering, knowledge engineering and platform architecture practices.

Support cross-product initiatives that depend on shared data infrastructure, semantic models and enterprise knowledge capabilities.

What success looks like

An agreed target architecture and transition roadmap for Falkor’s shared data and platform foundations.

Clear, adopted standards for data, metadata, ontology, search, knowledge graphs, workflow and integration services.

Reduced architectural fragmentation and stronger interoperability across products and platform capabilities.

Governed, scalable foundations that enable trustworthy AI‑assisted and decision‑support experiences.

Improved technical alignment between product, engineering, architecture and infrastructure stakeholders.

What we are looking for

Significant experience in software engineering, data platforms or distributed systems, including senior architecture or platform leadership responsibilities.

Proven ability to design and evolve enterprise‑grade, multi‑tenant or SaaS platform architectures.

Strong knowledge of distributed, event‑driven and API-based systems, including data pipelines, messaging, storage and integration patterns.

Experience with enterprise data architecture and at least one of the following areas: knowledge graphs and ontologies, enterprise search, semantic platforms or workflow orchestration.

Strong understanding of governance, security, lifecycle management, observability, scalability, reliability