Senior/ Lead Data Engineer

Carbon Data Solutions; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Carbon Data Solutions in the United States seeks a senior data engineer to build governed, AI-ready pipelines and lead end-to-end ingestion from ERP, clinical, customer, and operations sources into a governed lakehouse.

You will own transformation, modelling, semantic layer, data quality, and lineage for audit readiness, partnering with AI Engineers and Data Scientists in a global practice.

Qualifications

• 5-10 years of hands-on production data engineering, end-to-end delivery experience.
• Client-facing stakeholder management experience is preferred.
• Strong Python and SQL proficiency and modern data stack knowledge.

Responsibilities

• Build and operate end-to-end ingestion pipelines from ERP, clinical, customer and operational systems 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 cross-border rules).
• Build reusable accelerators and set engineering standards for the practice.

Skills

Python

SQL

dbt

Snowflake

Databricks

Airflow

Dagster

Iceberg

Delta Lake

Data governance

Vector stores

Azure

AWS

GCP

Tools

dbt

Snowflake

Databricks

Airflow

Dagster

Iceberg

Delta Lake

Job description

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