Informacje o stanowisku

We are looking for you if you have:

• very good knowledge of Spark and Python,

• hands-on experience building complex data pipelines,

• good understanding of ML models deployment and consumption patterns,

• ability to refactor, maintain, debug existing machine learning solutions,

• experience in deployment and provisioning automation tools (e.g., Docker, Kubernetes, CI/CD),

• problem-solving skills, being able to troubleshoot and optimize ML models.

Youll get extra points for:

• interest in banking and banking products,

• experience working in international, cross-functional teams,

• knowledge in Airflow, GCP (Dataproc, BigQuery, GCS), Azure pipelines.

Your responsibilities:

• develop and maintain a code base that produces ML models for different business units,

• refactor, simplify complexity continuously (e.g. batch to stream processing),

• improve data flow, establish new data sources and deployment,

• troubleshoot data issues, providing robust solutions to ensure optimal performance and reliability,

• continuously optimize our systems for performance and cost-effectiveness,

• document technical specifications, procedures, and outcomes,

• use Azure DevOps for CI/CD, task tracking, version control, and other DevOps practices.

Information about the team:

You will be part of an international highly skilled team of data scientists, analysts, and machine learning/data engineers. You will be working in an agile environment helping ING to achieve its goals on a global scale.

The role naming convention in the global ING job architecture will be “Engineer IV”.

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