Support national statistical offices in modernizing their IT architecture through the design, configuration, and deployment of a modular, open-source data lake technology stack. The role aims to develop in-house data engineering skills and provide guidance for sustainable modernization.
Five (5) years of experience. A minimum of five (5) years of progressively responsible experience in enterprise data management systems, data warehousing infrastructure, big data technologies, GIS analytics, and/or cloud-based data storage and data access solutions is required. Hands-on experience configuring and using open-source technologies, including data ingestion/pipeline tools (e.g. Apache NiFi), object/distributed storage solutions (e.g. MinIO, S3-compatible storage), collaborative analytics environments (e.g. JupyterHub/JupyterLab with Python and/or R), container orchestration/DevOps tools (e.g. Docker, Kubernetes, Helm, Git) is required. Experience working with National Statistical Offices, particularly within developing country settings, is desirable. Demonstrated experience in planning and implementing IT architecture solutions for complex statistical data production systems or data science projects. Demonstrated experience in agile project management and facilitation of IT trainings and workshops. Experience in coordination with various stakeholders is desirable.
Advanced university degree (Master’s degree or equivalent) in computer science, data science, data engineering, or related field. A bachelor’s degree in combination with seven (7) years of experience may be accepted in lieu of an advanced degree.
