Cloaked Analytics Engineer to own and build the semantic layer ensuring consistent metric definitions and relationships across the company. Collaborate with data and business teams to enable reliable AI-driven analytics.
Responsibilities
We're looking for an Analytics Engineer to own the semantic layer at Cloaked - the governed set of metrics, entities, and relationships behind every dashboard, self-serve analysis, and AI-driven answer across the company. Every number at Cloaked should mean the same thing, no matter who asks or which tool they use. You'll make that true.
This is a builder's role. You'll turn ambiguous business questions into durable, well-tested definitions that both people and AI agents can rely on, working closely with the Data team and partners across Product, Growth, Finance, and CX.
What will you do?
Design, build, and maintain the semantic layer, including metric definitions, dimensions, joins, and entity relationships across product, subscription, and lifecycle data
Build and maintain BI artifacts - models, explores, and dashboards - on top of the semantic layer for teams across the company
Build and curate certified metrics and queries that power AI-assisted, natural-language data querying, and improve answer accuracy over time
Partner with stakeholders to resolve conflicting metric definitions and document the agreed source of truth
Write clean, tested, version-controlled SQL and transformation code with data quality checks and clear documentation
Work closely with data engineering on upstream models, and with analysts on how the layer gets used
What skills and experiences will help you?
3-5 years of experience in analytics engineering, BI engineering, or a closely related role
Strong SQL and solid dimensional data modeling skills
Qualification
Required
3-5 years of experience in analytics engineering, BI engineering, or related role
Strong SQL and dimensional data modeling skills
Hands-on experience building semantic models in tools like Looker, Omni, dbt Semantic Layer, or Cube
Experience with dbt or similar transformation frameworks, Git workflows, and code review
Familiarity with cloud data platforms such as AWS/Athena, Snowflake, or BigQuery
Preferred
Experience building semantic models for LLM-driven analytics
