Senior Data Engineer

In the context of an Agentic AI Transformation, the Semantic layer is identified as a layer that sits between data sources and the end users or systems that consume them. Its role is to abstract data structures (tables, columns names, joins) into a business-friendly vocabulary (concepts, definitions, relationships, rules) that human and machines can interpret. is it identified as a key component that enables LLMs-based agents to interpret data in a trustworthy manner, hence it will support the scalability of Agentic AI across multiple use-cases.

Service deliverables (not limited to) : Entity exploration and implementation of a first approach to implementing the semantic layer (business vocabulary, ontologies, business process, data products, data product mapping, etc.), and related tools and technologies, based on selected Agentic use-cases in entities.

• Expertise in data platform engineering (install and manage data tools and services)

• Expertise in data engineering (incl. data modelling, data product, etc.)

• Expertise in Databricks

• Expertise in data management incl. data quality, semantics, ontologies, etc.

• Expertise in MS Fabric, Snowflake

• Expertise in large-scale, federated and complex companies

• Expertise in AI, LLMs, Agentic AI

• English environment is mandatory

Service Qualifications:

• Databricks certification