Full-Stack Engineer — Data & Analytics

What you will do

•    Data pipeline. Build the Discover module's data backbone: ingestion from open data, subscriptions and listeners into a managed lakehouse, using Azure data services (Microsoft Fabric and/or Data Factory, ADLS).

•    Lakehouse. Model and transform data through bronze/silver/gold layers; own data quality, freshness and incremental loads.

•    Analytics. Implement signal scoring and analytical queries that turn raw market data into ranked opportunities.

•    Front end. Build the analytics-facing surfaces — the Command Centre views, dashboards and persona-specific reporting — in React / Next.js over the same spine.

•    Search & retrieval. Wire the vector and search layer (Azure AI Search) that powers retrieval for the platform's AI agents, in partnership with the AI engineer.

•    Discipline. Keep the analytical and operational data paths cleanly separated, and the data models portable and well-documented.

Must-have

•    Full-stack capability (React / Next.js, TypeScript, Node.js) with genuine strength on the data side.

•    Strong SQL and data-modelling skills; experience building ETL/ELT pipelines and working with a lakehouse or warehouse.

•    Python for data work.

•    Able to reason about data quality, incremental loading, schema evolution and pipeline reliability — not just write queries.

•    Fluent with AI-assisted development.

Nice-to-have

•    Microsoft Fabric, Azure Data Factory, Synapse or Databricks experience.

•    dbt or similar transformation tooling; Parquet / DuckDB familiarity.

•    Azure AI Search or other vector-search experience; exposure to RAG pipelines.

•    Data governance / cataloguing (Microsoft Purview).

First 90 days, success looks like

•    A working ingestion-to-lakehouse pipeline feeding a live opportunity log in the Discover module.

•    First signal-scoring logic running and surfaced in the Command Centre.

•    Clean, documented, portable data models the rest of the team can build on.

How we work

Small, senior, AI-native team — you will use AI coding and agent tooling daily, and we expect you to be opinionated about where it helps and where it doesn't.

Iterative delivery in short cycles; we ship working software each cycle and build each module behind an API before its interface.

Azure-first and Microsoft-aligned (Entra ID, Azure DevOps/GitHub, Azure PaaS), with data resident in Malaysia and a strong audit and governance posture appropriate to a regulated capital-markets context.