Data Engineer

Key Responsibilities:

• Data Infrastructure Design: Lead the design and implementation of scalable data engineering solutions using Cognite Data Fusion (CDF).
• Integration & Data Modeling: Drive integrations and data modeling tasks, utilizing Cognite data connectors, SQL, Python/Java, and REST APIs.
• Custom Data Models: Develop custom data models for discovery, mapping, and cleansing of industrial data.
• Collaboration: Work with data scientists, project managers, and solution architects to deliver end-to-end projects.
• Code Reviews: Conduct code reviews and implement best practices to ensure the development of high-quality, maintainable code.
• Customer Support: Assist customers and partners with data engineering tasks using Cognite products.
• Product Development: Collaborate with Engineering and Product Management teams to prioritize customer needs and transform them into product offerings.

Required Skills & Qualifications:

• Education: Bachelor's or Master's degree in Computer Science or similar field, or relevant work experience in lieu of formal education.
• Experience: 3-5 years of experience in a customer-facing, data-intensive role.
• Data Pipeline Development: Proven experience delivering production-grade data pipelines using Python, SQL, and REST APIs.
• Domain Knowledge: Familiarity with data sources within the oil and gas and manufacturing industries is a plus.
• Distributed Computing: Experience with distributed computing tools such as Kubernetes and managed cloud services like GCP and/or Azure.
• DevOps Mindset: Experience with Git, CI/CD, and deployment environments, demonstrating a DevOps mindset.
• Problem-Solving: Ability to independently investigate and solve complex problems.
• Collaboration: Enjoys working in cross-functional teams and has strong communication skills.
• Humility and Knowledge Sharing: Able to ask for help when needed and enjoy sharing knowledge with peers.