We are looking for a Support Data Engineer with strong technical and analytical skills to join our growing data engineering support team. The ideal candidate will have hands-on experience with Cognite Data Fusion (CDF), Python, and SQL, coupled with a problem-solving mindset and a passion for customer success.
In this role, you will work closely with global customers and internal engineering teams to support, maintain, and optimize production-grade data environments. You will play a key role in troubleshooting complex data pipeline issues, improving reliability, and ensuring seamless data operations in live environments.
Key Responsibilities
Issue Troubleshooting & Customer Support
Investigate and resolve complex customer-reported issues related to data pipelines, integrations, and Cognite Data Fusion (CDF) functionality.
Debug data workflows, identify root causes, and provide permanent resolutions or effective workarounds.
Collaborate with customer and engineering teams to reproduce issues, validate fixes, and deliver stable production environments.
Analyze system errors, failed jobs, and performance bottlenecks across APIs, databases, and cloud integrations.
Proactively monitor and improve the reliability and performance of existing data pipelines.
Advanced & Enterprise-Level Support
Act as a technical point of contact for customer support cases, especially complex and high-impact incidents.
Perform in-depth troubleshooting, including custom code reviews, SQL performance tuning, and API analysis.
Manage on-call rotations for production support and ensure rapid response to critical issues within defined SLAs.
Build and maintain proactive monitoring and alerting systems (Grafana, Power BI, or equivalent).
Conduct root cause analyses (RCA) and drive continuous improvements in support processes.
Customer Enablement & Knowledge Sharing
Create technical documentation, troubleshooting guides, and reusable knowledge base articles.
Collaborate with product and engineering teams to relay feedback, suggest platform enhancements, and improve overall product stability.
Contribute to internal process improvements and customer onboarding initiatives to accelerate time-to-value.
Required Skills & Experience
Education: Bachelor's or Master's degree in Computer Science, Engineering, or related technical fields.
Experience: 3-7 years in a data-intensive or technical support role within SaaS, Data Platform, or Industrial Data environments.
Technical Expertise:
Strong hands-on skills in Python and SQL, including query optimization and data transformation logic.
Working experience with Cognite Data Fusion (CDF) -- data contextualization, ingestion pipelines, and APIs.
Proven ability to work with REST APIs, troubleshoot API integrations, and manage data workflows.
Exposure to cloud platforms (Azure or GCP), Kubernetes, and CI/CD pipelines.
Familiarity with monitoring tools like Grafana, Power BI, or similar dashboards.
Desirable Skills
Experience working with industrial data systems (Oil & Gas, Power, Manufacturing) or IIoT data models.
Knowledge of GraphQL, data quality frameworks, or automation scripting.
Hands-on understanding of cloud cost optimization, security best practices, and DevOps principles.
Key Attributes
Excellent problem-solving and troubleshooting abilities.
Strong English communication skills -- both written and verbal.
Customer-centric mindset, with a proactive approach to issue resolution.
Ability to work effectively under pressure and manage multiple priorities in fast-paced environments.
Job Type: Full-time
Work Location: In person
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