Lead ETL Developer / Technical Architect - Big Data & Credit Risk, Databricks

Make a difference in the financial life of millions of people: At Erste Digital you are co-creating the digital future, in which better financial health is possible. #believeinyourself

We are part of Erste Group – the largest banking group in Central and Eastern Europe with more than 2,500 branches and over 45,000 employees. Our more than 2,000 IT experts and enthusiasts are the bank's Digital Muscle.

What to do:

The Lead ETL Developer / Technical Architect is responsible for the architecture, design, development, and operational excellence of enterprise-scale data platforms supporting Credit Risk and Risk Analytics within Erste Group – Credit Risk Methods. This role combines deep hands-on expertise in data engineering with technical leadership responsibilities, driving the delivery of scalable, high-performance data solutions using Databricks, Spark, and cloud-native technologies. The individual defines technical standards, leads development teams, and works closely with Risk, Data, and Business stakeholders to enable trusted, governed, and analytics-ready credit risk data.

Technical Architecture & Solution Design:

• Define and own end-to-end architecture for Credit Risk data platforms.

• Design scalable ETL/ELT solutions leveraging Databricks Lakehouse architecture.

• Establish architectural standards, frameworks, and reusable design patterns.

• Review and approve technical designs, data models, and integration approaches.

• Drive technology roadmaps and modernization initiatives.

• Ensure solutions meet performance, scalability, resilience, and security requirements.

ETL & Data Engineering Leadership

• Lead development of large-scale ETL/ELT data pipelines across multiple source systems.

• Design and implement data ingestion frameworks for structured and semi-structured data.

• Develop high-performance Spark and Databricks solutions processing large volumes of banking risk data.

• Optimize data processing, storage, and compute performance.

• Establish development standards, coding practices, and engineering governance.

• Provide technical leadership and oversight throughout the software delivery lifecycle.

• Support production issue resolution and root cause analysis.

Data Architecture & Modelling

• Design enterprise data models for Risk Analytics and Credit Risk domains.

• Implement Lakehouse architectures using Databricks and Delta Lake.

• Define data layers, ingestion zones, curation processes, and consumption models.

• Implement metadata management and data lineage frameworks.