← All rolesFor companies

Newbridge

Senior/ Lead Data Engineer at Newbridge, via carbon.talent

One profile. Your skills are shown. You can apply to many roles.

Apply on the employer's page

via Himalayas · Open original listing

Our client is a global consulting firm operating from 30+ offices worldwide across the Americas, Europe, and Asia-Pacific.

Remote · SingaporePermanent

Stack

Data-EngineerLead-Data-EngineerData-ArchitectAnalytics-EngineerSenior-Lead-Data-EngineeringSenior-Data-Engineering

Must-haves

  • 5-10 years of hands-on production data engineering, end-to-end delivery experience, and client-facing stakeholder management.
  • Tech Stack:
  • Originally posted on Himalayas

About this role

Our client is a global consulting firm operating from 30+ offices worldwide across the Americas, Europe, and Asia-Pacific.

As a trusted advisor to the Office of the CFO, they partner with management teams and private equity sponsors to solve complex finance, accounting, and transformation challenges - free from audit independence constraints.

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).

Originally posted on Himalayas