Credit Risk Data Engineer — Data & Analytics Automation

ING Hubs Poland; Warszawa; On-site; PLN 107,000 - 201,000; Full time

Job summary

ING Hubs Poland is seeking a Data Scientist III in the Credit Infrastructure team to work on regulatory-compliant data engines and risk data landscapes. You will collaborate with analysts and modelers to implement robust data tooling and processes.

The role emphasizes agile collaboration, ongoing learning, and exposure to cutting-edge risk data architectures, all while ensuring alignment with latest policy updates and regulatory standards.

Qualifications

• Experience with Oracle Databases, SAS Data Integration Studio and SAS Enterprise Guide.
• Strong interest in data and systems, and regulation and technology, especially data lake architecture.
• Ability to communicate with both technical and non-technical audiences.
• Fluency in English is a must.
• Curiosity, willingness to learn, and taking on responsibility.

Responsibilities

• Drive technical activities with the team and ensure engines run smoothly and comply with policy updates.
• Liaise with Credit Risk Analysts and modelers to implement functional requirements.
• Understand the Credit Risk Data Landscape and models (PD, EAD, LGD) and Engines (DOD).
• Align priority and incident management; log incidents and communicate appropriately.
• Help build seamless data tooling and flows for Risk and business tribes.
• Be active in the digitalization of Risk and participate in various projects across the bank.
• Adopt a progressive, agile way of working and embrace new ideas.

Skills

Oracle Databases

SAS Data Integration Studio

SAS Enterprise Guide

Data lake architecture

Communication

English fluency

Curiosity and learning

Job description

ING Hubs Poland is seeking a Data Scientist III in the Credit Infrastructure team to work on regulatory-compliant data engines and risk data landscapes. You will collaborate with analysts and modelers to implement robust data tooling and processes.

The role emphasizes agile collaboration, ongoing learning, and exposure to cutting-edge risk data architectures, all while ensuring alignment with latest policy updates and regulatory standards.