Senior Data & AI Architect

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Serve as the data architecture representative for ERP, CRM, Finance, Supply Chain, and Laboratory Systems initiatives.

• Evaluate the downstream effects of changes, upgrades, and new implementations.

• Analyze source data prior to the commencement of integration.

• Develop and sustain conceptual, canonical, and semantic data models across Product, Customer, Supplier, Finance, Employee, and Quality domains.

• Generate reference architectures, integration blueprints, data contracts, and modeling standards for ingestion, medallion, and ELT patterns.

• Design and oversee the delivery of data models, semantic views, and consumption models within Snowflake.

• Direct dbt transformations, ensuring the accuracy of grain, joins, and metrics.

• Assess data engineering designs for compliance with architectural standards.

• Contribute to engineering guardrails and promote platform best practices.

• Advance the LGC enterprise ontology by connecting source metadata and relationships to regulated business concepts.

• Establish consistent and reliable definitions across the organization.

• Manage the lifecycle of semantic assertions from proposal and validation to approval and retirement.

• Convert semantic assertions into actionable Snowflake semantic models.

• Design governed data products and models that enable AI applications, including RAG and GraphRAG.

• Ensure data reliability, traceability, and suitability through governance, metadata management, MDM designs, and quality controls.

• Transform business requirements into architectural designs and documentation.

• Represent the Data & AI team in architectural and demand review forums.

• Collaborate effectively with both technical and non-technical stakeholders.

⛳️ Requirements

• Demonstrated experience in Enterprise Data Architecture, preferably within a complex, multi-system organization.

• Experience in direct engagement with ERP, CRM, Finance, or Lab Systems and translating business data needs into architectural designs.

• Strong proficiency in conceptual, logical, relational, and dimensional data modeling.

• Practical experience with Snowflake or a comparable cloud data platform.

• Hands-on experience with dbt for transformation design, testing, and lineage tracking.

• Advanced SQL skills across Snowflake, SQL Server, or Oracle.

• Experience in developing and testing analytical data models.

• Understanding of ETL/ELT processes, data integration, data pipelines, and medallion or lakehouse architectures.

• Proficiency in designing semantic models and understanding enterprise ontologies, data concepts, relationships, and business definitions.

• Knowledge of data governance, metadata management, lineage, and data quality, including controls for data utilized by AI and ML models.

• Experience in producing architecture documentation, data models, integration blueprints, and technical designs.

• Capability to clarify complex technical concepts to both technical and non-technical stakeholders.

• Experience in constructing enterprise ontologies or knowledge graphs using SPARQL or SHACL would be advantageous.

• Practical experience with Snowflake Semantic Views or Cortex would be beneficial.

• Understanding of API, event-driven, and file-based integration patterns and platforms like MuleSoft would be advantageous.

• Familiarity with Master Data Management (MDM) would be beneficial.

• Knowledge of enterprise architecture tools such as Erwin Evolve would be beneficial.

• Experience in supporting AI/ML applications or working with RAG and GraphRAG would be advantageous.

• Background in life sciences, regulated industries, or global organizations would be beneficial.

• Relevant enterprise architecture, data architecture, or cloud platform certifications would be advantageous.

🏝️ Benefits

• An inclusive work environment where all individuals can compete and succeed based on their merits.

• A commitment to non-discrimination and appreciation for employees' unique talents.