Key responsibilities include: • Building and configuring semantic layer components, including LookML models, dbt metrics, and dimension and measure definitions • Contributing to knowledge graph schema design and populating graph databases with domain-relevant data • Writing and testing data pipelines that feed context platforms with structured and unstructured data • Documenting semantic objects, context contracts, and data dictionaries for client use • Supporting discovery workshops focused on mapping enterprise data assets and knowledge flows • Assisting in the evaluation and configuration of knowledge and context platform tooling. Required: • 3-5 years of experience in data engineering, analytics engineering, or data architecture • Hands-on experience with dbt, SQL, and at least one cloud data platform (e.g., BigQuery, Snowflake, Redshift) • Understanding of semantic modeling concepts such as dimensions, measures, metrics, and hierarchies • Strong documentation skills and attention to data quality.