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 non-technical audience,
You'll get extra points for:
- financial knowledge about transaction analysis,
- experience of applying data analysis and data science in 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 to design and build the data pipelines for one of many use cases catering stakeholder requirements, collaborate with the data analysts and UX researchers to create the best user experience and insights for our users. Your day-to-day activities can look like this: implementing new features in Kedro/PySpark, testing them in Apache Airflow, deploying it 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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