Analytics Engineer: Build Semantic Layer & Knowledge Graph

Newbridge; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Newbridge is seeking an Analytics Engineer to craft a production-grade Semantic Layer that serves as the single source of truth for analytics across the platform. You will design Graph-based models (Knowledge Graph) and expose them via GraphQL/REST APIs, powering BI and AI-driven experiences for thousands of users while ensuring governance, security, and high performance.

Deep collaboration with Data Eng, Product, and Frontend teams will be essential to deliver self-serve data products and

Qualifications

• Semantic Layer experience in production environments (Cube.js or dbt Semantic flow)
• Graph data modeling and exposure via GraphQL/REST APIs
• Advanced SQL and dimensional modeling with modern data warehouses

Responsibilities

• Design and own the end-to-end Semantic Layer as source of truth.
• Architect Graph-based Knowledge Graph models for context and lineage to metrics.
• Build secure, high-performance GraphQL/REST APIs for analytics.
• Own pre-aggregation strategy, caching, and query tuning.
• Implement governance and multi-tenant access controls.
• Collaborate with Data Eng, Product, and Frontend to deliver self-serve data products.
• Maintain documentation and data quality for the semantic layer.

Skills

Cube.js / CubeCore

dbt Semantic flow

Graph data modeling

Neo4j / Neptune / TigerGraph / Memgram

GraphQL API

Knowledge Graphs

Graph integration with semantic layer

SQL

Dimensional modeling

Modern Data Warehouse

dbt transformations

Row-Level Security

BI integration (Superset Looker PowerB

Tools

Snowflake

BigQuery

Databricks

Redshift

Job description

Newbridge is seeking an Analytics Engineer to craft a production-grade Semantic Layer that serves as the single source of truth for analytics across the platform. You will design Graph-based models (Knowledge Graph) and expose them via GraphQL/REST APIs, powering BI and AI-driven experiences for thousands of users while ensuring governance, security, and high performance.

Deep collaboration with Data Eng, Product, and Frontend teams will be essential to deliver self-serve data products and