Key Responsibilities :

- Own and design the enterprise semantic layer, data models, and graph schema.

- Develop dimensional models using star schemas, conformed dimensions, and slowly changing dimensions.

- Design and maintain Snowflake semantic views, named metrics, and governed analytical models.

- Develop and manage Cortex Analyst semantic models and the Verified Query Repository.

- Design graph data models including nodes, edges, ontologies, and taxonomies.

- Drive enterprise-scale entity resolution, alias mapping, and relationship modelling.

- Ensure SQL correctness and adherence to a numbers-from-code discipline.

- Design and implement row access policies and collaborate with DevOps on data security and governance.

- Develop transformation workflows using dbt Core, SQL, and Python.

- Establish and maintain SQL quality standards using SQLFluff or equivalent linting tools.

- Collaborate with Data Engineering, Analytics, DevOps, and business teams to ensure consistent and trusted data definitions.

Must-Have Skills :

- Strong experience in Analytics Engineering and Data Modelling.

- Hands-on expertise in dimensional modelling, including star schema, conformed dimensions, and slowly changing dimensions.

- Strong experience with Snowflake semantic views, named metrics, row access policies, and masking policies.

- Experience with Cortex Analyst semantic models and Verified Query Repository.

- Strong experience in graph data modelling, including node and edge design.

- Experience with ontology/taxonomy development and enterprise-scale entity resolution.

- Strong experience with alias mapping and relationship modelling.

- Hands-on experience with dbt Core and advanced SQL.

- Experience with SQLFluff or equivalent SQL linting tools.

- Strong Python skills for data transformation and modelling.

- Strong understanding of data governance, security, and SQL correctness.

Preferred Skills :

- Exposure to GCP BigQuery.

- Experience working with graph databases or graph-based analytics platforms.

- Experience in large-scale enterprise data environments.

- Strong understanding of DevOps practices for data platforms and security controls.