Financiële diensten
DevOps Engineer for Data Engineering & Automated ETL/Archiving Pipelines
Vandaag toegevoegd
Sommige details van deze opdracht zijn niet publiek beschikbaar.
Word gratis lidOver de opdracht
Role overview
Dev Ops Engineer position within a large Dutch retail and commercial bank. The assignment focuses on building and maintaining automated data pipelines and searchable archive capabilities. Work includes implementing ETL architecture to transfer structured and non-structured data into an object-store backed archive, supporting regulatory and compliance-related use cases, and enabling applications to ingest and present archived data in searchable formats. Secure search interfaces and analytics built on top of the pipeline data are part of the scope.
Key responsibilities
The role delivers standardized, automated data pipelines through coding, testing, documentation, and ongoing maintenance. It covers designing and building infrastructure for extraction, transformation, and loading across multiple data sources, as well as developing bespoke archive functionality and a generic framework for ingesting decommissioned application data into searchable archives. The engineer also builds analytics tools using the pipeline to support business metrics such as customer acquisition and operational efficiency. Testing, documentation, and handover to the customer are included, along with proactive communication of progress and risks to the team to meet aggressive delivery timelines.
Working arrangement
The position is performed on-site at a bank location in Utrecht.
Eisen
- English mandatory
- In-depth experience of developing Python or PowerShell scripts across Windows and Linux platforms
- Experience with at least one of these object-oriented languages: C#, JavaScript or .Net
- Experience of UI development, ideally with React
Wensen
- Experience with creating playbooks in Ansible Automation Platform
- Working knowledge and experience working with MSSQL and Oracle databases
- Knowledge of Hitachi Content Platform
- Knowledge of Solr