Analytics Engineer - Semantic Layer [Cube.js / dbt Semantic Layer + Graph]

Our client is building a next-generation data product platform where analytics is not an afterthought - it IS the product. We are looking for an Analytics Engineer who has built a production-grade Semantic Layer using Cube.js or dbt Semantic Layer and has strong experience working with Graph.

You will own the metrics store + graph layer that powers BI, and AI-driven experiences for thousands of users.

Must-Have Skills [Non-Negotiable]:

1. Semantic Layer Expertise - Must have ONE:

• Track A - Cube.js / CubeCore: 2+ years in production building cubes, views, pre-aggregations, rollups, blending, securityContext, multi-tenancy, and Cube Store. Experience with Cube Cloud deployment on Docker/K8s.
• OR Track B - dbt Semantic Layer: 2+ years in production building semantic models, metrics [simple/derived/cumulative/conversion], saved queries, and exposing via GraphQL/JDBC APIs. Experience with dbt Cloud/Core.

2. Graph Expertise - Must Have:

• Hands-on experience in Graph data modeling and implementation.
• Proficiency in at least one: Neo4j / Amazon Neptune / TigerGraph / Memgraph OR GraphQL API architecture
• Strong knowledge of Graph query languages: Cypher / Gremlin / GraphQL
• Experience building Knowledge Graphs, Metrics Graphs, or Property Graphs for analytics use cases
• Understanding of how to integrate graph context with semantic/metrics layer

3. Core Analytics Engineering:

• Expert-level SQL and Dimensional Data Modeling [Star, Snowflake, Data Vault]
• Strong hands-on with Modern Data Warehouse: Snowflake / BigQuery / Databricks / Redshift
• Expert in dbt for transformation
• Experience building Row-Level Security, performance optimization, and caching strategies for sub-second analytics
• Experience powering BI tools or customer-facing embedded analytics[Superset][Metabase][Looker][PowerBI]

Key Responsibilities:

1. Design, build and own the end-to-end Semantic Layer - the single source of truth for all business metrics.
2. Architect and build Graph-based models[Knowledge Graph] to add context, relationships, and lineage to metrics.
3. Build secure, high-performance APIs[GraphQL/REST] for internal and embedded analytics consumption.
4. Own pre-aggregation strategy, caching, and query performance tuning.
5. Implement enterprise-grade governance, security, and multi-tenant access control.
6. Partner with Data Engineering, Product, and Frontend teams to deliver self-serve data products.
7. Own documentation, data quality, and adoption of the semantic layer across the organization.

Tech Stack: Cube.js, dbt, Snowflake/BigQuery, Neo4j/GraphQL, Airflow, dbt, Kubernetes, TypeScript/Node.js, Python, Superset/Looker

Nice to Have:

• Experience with BOTH Cube.js AND dbt Semantic Layer - or migration experience
• Graph + Vector DB experience for GenAI / RAG use cases
• Experience with Apollo Federation
• Prior experience in B2B SaaS building external-facing analytics
• Contributions to Cube.js / dbt open source