Senior /Data Engineer - Kuala Lumpur

Newbridge; Kuala Lumpur; On-site; MYR 180,000 - 320,000; Full time

Job summary

Newbridge in Kuala Lumpur is seeking a senior Data Engineer to architect and manage end-to-end data pipelines that transform fragmented client data into AI-ready assets. You will oversee transformations, semantic layers, and master data quality while implementing governance and security by design across cloud environments.

You will collaborate with AI Engineers and Data Scientists to deliver trusted data assets, embeddings, and RAG corpora for enterprise AI initiatives, ensuring audit readiness

Qualifications

• 5-10 years of hands-on production data engineering, end-to-end delivery experience, and client-facing stakeholder management.

Responsibilities

• Build and operate end-to-end ingestion pipelines from ERP, clinical, customer and operational systems (batch + streaming) into a governed lakehouse.
• Own transformation, modelling, and semantic layer to ensure consistent business logic across BI and AI.
• Prepare and serve AI-ready data - curated datasets, embeddings, and RAG corpora.
• Own data quality, master data / entity resolution, and end-to-end lineage for audit readiness.
• Embed governance, privacy & security by design (PDPA and APAC data residency / cross-border rules).
• Build reusable accelerators and set engineering standards for the practice.

Skills

Python

SQL

Cloud

Vector stores

Data governance

Data modelling

ETL

dbt

Snowflake

Databricks

Airflow

Dagster

Iceberg

Delta Lake

Tools

dbt

Snowflake

Databricks

Airflow

Dagster

Iceberg

Delta Lake

Azure

AWS

GCP

Job description

The Mandate:

You will build governed, audit-ready pipelines that turn fragmented client data into trusted, AI-ready assets. This is a central, load-bearing role working alongside AI Engineers and Data Scientists.

Key Responsibilities:

• Build and operate end-to-end ingestion pipelines from ERP, clinical, customer and operational systems (batch + streaming) into a governed lakehouse.
• Own transformation, modelling, and semantic layer to ensure consistent business logic across BI and AI.
• Prepare and serve AI-ready data - curated datasets, embeddings, and RAG corpora.
• Own data quality, master data / entity resolution, and end-to-end lineage for audit readiness.
• Embed governance, privacy & security by design (PDPA and APAC data residency / cross-border rules).
• Build reusable accelerators and set engineering standards for the practice.

Must Have:

5-10 years of hands-on production data engineering, end-to-end delivery experience, and client-facing stakeholder management.

Tech Stack:

Expert Python & SQL, dbt, Snowflake / Databricks, Airflow / Dagster, Iceberg / Delta Lake, plus strong understanding of data governance, vector stores, and cloud (Azure / AWS / GCP).