Analytics Engineer: Build Trusted Data for Self‑Serve Analytics

Endowus; Singapore; Hybrid; SGD 90,000 - 150,000; Full time

Job summary

Endowus is hiring its first Analytics Engineer to build data models and metric definitions powering analytics across the company. You will own dbt models, automated tests, and the semantic layer to enable core teams such as Product, Marketing, and Operations to access reliable data.

You will design models for client portfolios, fund transactions, and multi-currency valuations across two markets, gaining hands-on experience with governed data foundations as AI workflows expand.

Qualifications

• 1–3 years of hands-on SQL experience, using CTEs, window functions and nested structures to build performant, reusable logic.
• Structured analytics approach using version control, code reviews, and testing to build maintainable models.
• View source data, transformations, semantic layers, and BI as one connected system, anticipating downstream impacts.
• Clear specs, documentation, and metric definitions, refining AI outputs into concise explanations.
• Active use of AI tools to accelerate work, driven by curiosity about data and business.
• Thrive on loosely defined problems; gather context and state assumptions to move forward.

Responsibilities

• Model the data end-to-end with dbt models; collaborate with Data Engineering and software engineers to create clean, intuitive models for business teams.
• Make the models trustworthy with automated testing, freshness monitoring, and dbt documentation.
• Govern the metrics by standardising core definitions and establishing a single source of truth for key numbers.
• Enable self-serve analytics by designing models and semantic definitions for a dbt-native BI layer.

Skills

SQL depth

Engineering mindset

Systems thinking

Clear technical writing

AI-native curiosity

Comfort with ambiguity

Tools

dbt

Git

Job description

Endowus is hiring its first Analytics Engineer to build data models and metric definitions powering analytics across the company. You will own dbt models, automated tests, and the semantic layer to enable core teams such as Product, Marketing, and Operations to access reliable data.

You will design models for client portfolios, fund transactions, and multi-currency valuations across two markets, gaining hands-on experience with governed data foundations as AI workflows expand.