ETL Engineer (Python)

Role and responsibilities

• Develop Cognite Data Fusion - a robust, state-of-the-art SaaS for industrial data
• Create ETL applications that onboard data from various source system (SAP, OPC-UA, PI, cloud databases, file storages) into Cognite Data Fusion
• Build scalable ETL tools in Python, together with talented colleagues that love to build reliable integrations
• Integrate with Cognite’s graph database technology that bases on PostgreSQL and Elasticsearch
• Bring data into our industrial knowledge graph, realizing Cognite’s vision of a safer and more efficient industrial future
• Work with customer facing teams to ensure a delightful data onboarding experience, and enable our users to solve complex real-world problems that have yet to be solved before
• Collaborate with stakeholders and great colleagues that are subject matter experts on industrial data and various source systems
• Be actively involved in product and technical decisions

We believe most of these should match your experience

• Solid experience with building ETL applications using Python, or another backend language with a strong motivation to learn Python
• Understanding of modern database technologies, particularly PostgreSQL
• Proven experience writing integrations between systems or in the ETL space. Preferably experience with source systems such as PI, OPC-UA, WITSML, IP21, SAP or file storages such as  Sharepoint, Documentum, AzureBlobStorage
• Passion for graph processing, databases, performance engineering, or distributed systems
• Broad experience with DevOps practices such as CI/CD and Infrastructure as code
• Strong troubleshooting and problem-solving skills; ability to track down information in logs, traces, and metrics and take appropriate action based on findings
• Solid understanding of monitoring tools such as Prometheus and Grafana
• Comfortable working with Open-Source community - request features, fix issues
• Excellent communication and collaboration skills

Additional experience that is an advantage, but not required

• Experience with large Cloud deployments on any of AWS, GCP, or Azure; build, test, deploy, and monitor software in a multi-cloud Kubernetes environment
• Broad experience with DevOps practices such as CI/CD and Infrastructure as code
• Solid understanding of monitoring tools such as Prometheus and Grafana
• Previous experience using FastAPI to build Python Web APIs