Data Engineer

About Indicium AI 

Indicium AI is trusted by the world's leading enterprises to deliver AI into production at scale. We are a global AI-native consultancy with proven experience across Financial Services, Energy & Utilities, Healthcare & Life Sciences, Retail & CPG, and Manufacturing. From strategy, to build, to business outcomes, we unlock value from AI with unmatched clarity, speed, and capability.

Powered by 600+ AI experts serving 50+ enterprise clients from 5 global locations, we work side-by-side with top partners - including Anthropic, Databricks, AWS, OpenAI, and Microsoft - to deliver modern AI with speed and measurable impact.

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Opportunity**

As a Principal Data Engineer at Indicium AI, you will join a team of AI and data practitioners delivering enterprise-grade information architecture for leading organisations across Europe. Working within complex client engagements, with a strong focus on Financial Services, you will lead data modelling and semantic architecture, shape data platform standards, and guide engineering teams in building AI-ready data products. This is an opportunity to operate as a true design authority, driving architectural rigour while making a measurable impact on clients' data strategies from day one.

Responsibilities

Data Modelling & Architecture

• Lead and contribute to conceptual, logical, and physical data model design aligned to client architectures, translating business requirements into rigorous data structures in collaboration with engineering and domain teams.
• Govern and maintain data models in appropriate tooling, enforcing naming conventions, domain standards, and versioning across source, integration, and consumption layers.
• Define and steward canonical data entities and lineage, and guide teams on the design and effective use of semantic data models, including their application to agentic AI solutions.

Semantic & Knowledge Modelling

• Design and maintain semantic models to support agentic-AI capabilities, integrating semantic layers with business glossaries, data catalogues, and lineage tooling.
• Help develop ontologies, taxonomies, and controlled vocabularies underpinning enterprise metadata and search, and define semantic modelling standards and patterns to ensure consistent meaning, interoperability, and AI readiness across data products.
• Guide and govern the creation of data domains aligned with the client's underlying business capabilities.

Data Engineering & Platforms

• Design data product schemas across platforms including Azure, Snowflake, and Databricks, encompassing Delta Lake structures and interoperable patterns, and define architectural guardrails for performance, scalability, security, and cost efficiency.