On behalf of our client, we are seeking a passionate

Data Engineer (with GCP & BigQuery experience)

to drive a high-stakes cloud transformation within their "Corporate Stock Valuation" agile team.

The core mission of this position is to lead the modernization of their financial data infrastructure, migrating mission-critical processes from legacy systems (Teradata) to Google Cloud (BigQuery). Because the data involved represents 30% of the client's total balance sheet, this role is highly impactful: your solutions will directly guarantee the accuracy, speed, and reliability of their general financial reporting and decision-making.

Our client is looking for a proactive, team-oriented tech professional—fluent in both

English and German —who brings a strong agile and DevOps mindset. The ideal candidate has a deep understanding of cloud architecture, data integration, and automation, and thrives on solving complex challenges. More than just a developer, the client needs a strategic partner who can collaborate seamlessly with financial stakeholders,



bridging the gap between business needs and resilient, scalable technical solutions.

Key languages:
Full Professional Level of English
Full Professional Level of German

Main responsibilities:
Modernize Core Architectures:

Architect and optimize the transition of our financial engine from legacy Teradata to GCP (BigQuery), leveraging modern cloud capabilities.
Develop Critical Business Simulations:

Design and execute complex financial simulations that empower business leadership during key operational events.
Drive Continuous Enhancement:

Iterate on existing data pipelines and solutions to ensure long-term stability and performance.
Empower Your Peers:

Elevate team capabilities through peer code reviews, technical guidance, and knowledge sharing.
Translate Finance into Code:

Collaborate directly with Product Owners and Finance experts to turn real-world financial logic into seamless, automated solutions.
Evolve Deve

📌 Software Engineer (Madrid)
🏢 Babel Profiles
📍 Madrid