About the role
We are looking for a strong Analytics and Ontology Engineer who can bridge the gap between business, data, and AI. This is not a traditional data engineering role. We need someone who can understand how a business operates, model that knowledge into data structures, create meaningful lineage, and build dashboards that drive decisions. You will work closely with product, engineering, and business teams to define the semantic foundation of our platform.
Responsibilities:
- Design and maintain the business ontology for global trade and logistics.
- Translate business processes into entities, relationships, metrics, and knowledge graphs.
- Build end-to-end data lineage from source systems to executive dashboards.
- Create semantic models that power analytics, reporting, and AI agents.
- Design dashboards that explain business performance, bottlenecks, and opportunities.
- Establish metric definitions and ensure consistency across the organisation.
- Build scalable data models and transformation pipelines.
Requirements:
- 5-7 years of experience in ontology engineering, data engineering, or data analytics.
- Strong SQL and data modelling skills.
- Experience with modern analytics engineering tools such as dbt or SQLMesh.
- Deep understanding of dimensional modelling, semantic layers, and business metrics.
- Experience with BI platforms such as Metabase, Tableau, Power BI, Looker, or Superset.
- Familiarity with metadata, lineage, and governance tools such as DataHub or OpenMetadata.
- Understanding of knowledge graphs, ontologies, and graph databases is a strong plus.
- Ability to think from first principles and model complex business domains.
Past background/skills/competencies:
- Background in business analytics.
- Have an engineering background (backend or full stack preferred) required for articulating business asks/problems into technical requirements.
- AI-first thinking.