Senior /Lead Data Engineer

NEWBRIDGE ALLIANCE PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

NEWBRIDGE ALLIANCE PTE. LTD. is seeking a senior data engineering professional to build governed, audit-ready pipelines that transform fragmented client data into trusted AI-ready assets.

You will collaborate with AI Engineers and Data Scientists in a central, load-bearing role. Responsibilities include owning end-to-end ingestion pipelines, data transformation, AI-ready data assets, data quality and lineage, and governance by design across cloud environments.

Qualifications

• 5–10 years of hands-on production data engineering, end-to-end delivery, and client-facing stakeholder management.
• Experience building governed data pipelines with auditability and lineage.
• Strong Python and SQL proficiency with modern data stack exposure.
• Experience with PDPA/APAC data residency is a plus.

Responsibilities

• Build and operate end-to-end ingestion pipelines from ERP, clinical, customer, and operations systems.
• Own transformation, modelling, and semantic layer for consistent business rules across BI and AI.
• Prepare and serve AI-ready data, including embeddings and RAG corpora.
• Own data quality, master data management, and end-to-end lineage for audit readiness.
• Embed governance, privacy, and security by design (PDPA and APAC data residency / cross-border rules).
• Build reusable accelerators and set engineering standards for the practice.

Skills

Python

SQL

Data governance

Tools

dbt

Snowflake

Databricks

Airflow

Dagster

Iceberg

Delta Lake

Azure / AWS / GCP

Job description

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).