Senior Data Engineer- AI Data Platform - up to €125k

We Source Talent; Netherlands; Remote; EUR 90,000 - 120,000; Full time

Job summary

We Source Talent is seeking a remote Senior Data Engineer for a pre-Series A startup in the finance sector. You will own production Python pipelines and data integration, enabling AI-driven agents with graph databases and vector stores.

You will work directly with the CTO on architecture, expanding data providers, and mentoring a core data team as part of a 60/40 IC/lead split. Strong Python and cloud experience are required.

Qualifications

• 6-10 years in data engineering, ML systems or backend-heavy roles.
• Strong Python for production ETL/ELT pipelines.
• Conceptual grasp of graph databases and vector stores.
• Cloud platform experience, ideally GCP, plus DevOps/IaC, CI/CD and security controls (IAM, Secret Manager, SOC2).
• Experience supporting ML or AI-powered products in production.
• Self-reliance - you solve problems without waiting to be told how.

Responsibilities

• Build production Python pipelines loading customer data into a graph and vector store (SurrealDB).
• Add new data providers and connectors (Snowflake, ERP, accounting and billing systems).
• Manage the data ontology for accurate AI retrieval across multi-entity financial data.
• Own end-to-end data, DevOps and infrastructure responsibilities.

Skills

Python

ETL/ELT pipelines

Graph databases

Vector stores

GCP

DevOps/IaC

Security controls

ML in production

Self-reliance

Tools

SurrealDB

Snowflake

Cloud platforms

Job description

A pre-Series A startup building autonomous agents within the finance sector are hiring a remote Senior Data Engineer.

Founders come from Uber and Airtable alongside a 5x CFO. You'll report directly to the CTO in a flat, low-ego team.

What you’ll own:

• Production Python pipelines loading customer data into a graph and vector store (SurrealDB)
• New data providers and connectors ,Snowflake, ERP, accounting and billing systems
• The data ontology itself, so AI retrieval and agent reasoning stay accurate across multi-entity financial data
• End-to-end ownership spanning data, DevOps and infrastructure
• A shift from ~80% IC toward a 60/40 split, with the 40% mentoring a core data team of four and shaping long-term architecture

What you’ll bring:

• 6-10 years in data engineering, ML systems or backend-heavy roles (flexible for strong candidates at 3-4)
• Strong Python for production ETL/ELT pipelines
• Conceptual grasp of graph databases and vector stores
• Cloud platform experience, ideally GCP, plus DevOps/IaC, CI/CD and security controls (IAM, Secret Manager, SOC2)
• Experience supporting ML or AI-powered products in production
• Self-reliance - you solve problems without waiting to be told how