Informacje o stanowisku

We are looking for you, if you:

• have experience with Apache Airflow, Spark, Python,
• experience in building Azure, GitLab CICD pipelines,
• have hands-on experience building complex ETL data pipelines,
• have experience in setting up and optimizing both SQL and noSQL data stores (MS-SQL, Hive), as well as familiarity with object storage services (e.g., S3),
• can manage accesses, data, and code repository (code review and testing on Azure DevOps),
• have excellent communication skills, including being able to explain technical terms to a non-technical audience.

Youll get extra points for:

• financial knowledge about transaction analysis,
• experience of applying data analysis and data science in the financial sector.

Your responsibilities:

Your passion is to work with the latest concepts and technologies in the field of Data Engineering. As an engineer, you will be responsible for designing and building the data pipelines for various use cases catering to stakeholder requirements, collaborating with data analysts and UX researchers to create the best user experience and insights for our users. Your day-to-day activities may include: implementing new features in Kedro/PySpark, testing them in Apache Airflow, deploying them in our in-house platform running on Kubernetes, as well as optimizing the data in the permanent data store.

Information about the squad:

The Analytics Engineering team is a team of 80+ people (and growing rapidly) that has the mission to make ING data-driven. We do this by combining Big Data technology with Data Science to deliver high-value solutions and products for our organization. We work in a fun and creative environment and we’re dedicated to bringing out the best in both each other and our projects.

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