Senior Data & AI Architect

LGC is an international life sciences tools company, building leading positions in sustainably growing markets. It provides reference materials, genomics solutions and analytical testing products and services, based on its innovation and intellectual property. It works with customers in the pharmaceuticals, agricultural biotechnology, food, environment, and sports sectors as well as with governments and academia to achieve excellence in investigative, diagnostic and measurement science.

LGC has sites across the globe including the UK, the US, Europe, China, and Canada. LGC Group supports the development of clinical diagnostic kits, genomics-based therapeutics, and drought-resistant crops with its genomics capabilities. It offers the most comprehensive range of reference materials available - in total over 100,000 products for analytical laboratories to choose from, ensuring safety of many every day and essential products. Its offering is underpinned by its heritage and expertise in regulation, accreditation, and standard setting. It helps customers conform to international statutory and regulatory standards. Science is at the heart of all it does - for a safer world.

Are you an experienced Data Architect who enjoys both enterprise-level architecture and hands-on technical design? Do you want to keep our source systems, data platform and AI use cases working together coherently?

At LGC, we're looking for a Senior Data & AI Architect to take on the day-to-day running of our enterprise data architecture, working under the direction of the Head of Enterprise Data & AI Architecture.

This is a hands-on role that combines classic enterprise data architecture, keeping data coherent across ERP, CRM, Finance, Supply Chain and Laboratory Systems, with technical data architecture on our Snowflake platform, including dbt and integration patterns. You will also help drive our strategic semantic architecture and enterprise ontology, so that analytics and AI are built on trusted, consistent business meaning.

We're looking for someone who can see the bigger picture but isn't afraid to roll up their sleeves and get into the detail.

What you’ll be doing:

• Engage with source systems: Act as the data architecture representative in ERP, CRM, Finance, Supply Chain and Laboratory Systems programmes, assessing the downstream impact of changes, upgrades and new implementations, and profiling source data before integration begins.
• Design enterprise data models: Create and maintain conceptual, canonical and semantic data models for key domains such as Product, Customer, Supplier, Finance, Employee and Quality.
• Define patterns and blueprints: Produce reference architectures, integration blueprints, data contracts and modelling standards for ingestion, medallion and ELT patterns.
• Work with Snowflake and dbt: Design and guide delivery of data models, semantic views and consumption models in Snowflake, with dbt transformations tested for grain, joins and metric correctness.
• Guide engineering teams: Review data engineering designs for conformity with architectural standards and contribute to engineering guardrails and platform best practice.
• Shape our semantic architecture and ontology: Help develop the LGC enterprise ontology by linking source metadata and relationships to governed business concepts, and establish consistent, trusted definitions across the organisation. Manage a controlled lifecycle to propose, validate, approve and retire semantic assertions, and turn them into practical Snowflake semantic models.
• Support AI innovation: Design governed data products and models that enable AI applications, including RAG and GraphRAG.
• Drive data quality and governance: Ensure data is reliable, traceable and fit for purpose through data governance, metadata management, Master Data Management designs and quality controls.
• Turn complex ideas into practical solutions: Translate business requirements into clear architectural designs and documentation, represent the Data & AI team in architecture and demand review forums, and work closely with technical and non-technical stakeholders.

• Proven experience in Enterprise Data Architecture, ideally within a complex, multi-system organisation.
• Experience engaging directly with source systems such as ERP, CRM, Finance or Lab Systems, and translating business data requirements into architectural design.
• Strong expertise in conceptual, logical, relational and dimensional data modelling.
• Hands-on experience with Snowflake or a similar cloud data platform.
• Hands-on experience with dbt for transformation design, testing and lineage.
• Advanced SQL skills across platforms such as Snowflake, SQL Server or Oracle, and experience developing and testing analytical data models.
• A solid understanding of ETL/ELT, data integration, data pipelines, and medallion or lakehouse architectures.
• Experience designing semantic models, with a good understanding of enterprise ontologies, data concepts, relationships and business definitions, and how governed semantic models support analytics and AI.
• Knowledge of data governance, metadata management, lineage and data quality, including controls for data used by AI and ML models.
• Experience producing architecture documentation, data models, integration blueprints and technical designs.
• The ability to explain complex technical concepts clearly to both technical and non-technical stakeholders.

The following experience would be beneficial:

• Experience building enterprise ontologies or knowledge graphs, using semantic technologies such as SPARQL or SHACL.
• Hands-on experience with Snowflake Semantic Views or Cortex.
• Understanding of integration patterns (API, event-driven, file-based) and platforms such as MuleSoft.
• Exposure to Master Data Management (MDM).
• Familiarity with enterprise architecture tools such as Erwin Evolve.
• Experience supporting AI/ML applications or working with RAG and GraphRAG.
• A background in life sciences, regulated industries or global organisations.
• Recognised enterprise architecture, data architecture or cloud platform certifications.

Our values:

Passion: Pride in our achievements engenders passion for our work and it translates into our ambition to make the world a safer place.

Curiosity: We constantly look forward to what's next: our curiosity for today's discoveries makes tomorrow's innovations possible.

Integrity: A commitment to high ethical standards has been at the heart of LGC since we started testing the integrity of products in 1842.

Brilliance: We strive to be the very best in everything we say and do. We exceed customers' expectations through innovation and pioneering science.

Respect: We respect gender, age, nationality, religion and individuality - our diversity is our strength.

We are committed to ensuring that every job applicant and employee is valued for their individual talents. We strictly prohibit discrimination on the basis of age, disability, race, colour, ethnic or national origin, sex, sexual orientation, gender reassignment, marital or civil partnership, pregnancy or parental status, religion, or belief. We proudly support an inclusive work environment where everyone can compete and succeed based on their merits.

For more information about LGC, please visit our website www.lgcgroup.com

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