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About the role
Key ResponsibilitiesTroubleshooting Issues & Customer Support:Investigate and debug complex customer-reported issues related to data pipelines, integrations, data models, and Cognite Data Fusion (CDF) functionality.Work with customer teams to understand production incidents, reproduce issues, and implement fixes or workarounds.Analyze data failures, system errors, and unexpected behaviors across API integrations, custom code, and third-party data sources.Proactively identify bottlenecks, configuration mismatches, or anomalies to improve data pipeline reliability and performance.Collaborate with engineering and product teams to escalate platform issues and contribute to long-term resolutions.Advanced and Enterprise-Level Support:Serve as the technical point of contact for high-priority customer support cases.Perform in-depth troubleshooting and diagnostics, including custom code reviews and integration issues with third-party data sources.Engage in regular case reviews, root cause analysis, and progress updates aligned with customer SLAs.Participate in on-call rotations to ensure 24/7 coverage and quick resolution of critical issues.Implement proactive monitoring and alerting systems to identify and address potential issues before they escalate.Customer Enablement & Knowledge Sharing:Develop clear documentation, how-to guides, and knowledge base articles to improve issue resolution efficiency and reduce repeat tickets.Work closely with internal product and engineering teams to relay customer feedback and prioritize product improvements.Required Qualifications & SkillsExperience:3+ years in a data-intensive, customer-facing role, with experience in technical support in a SaaS or data platform environment, ideally in a Tier 2/3 or engineering-focused support function.Proven experience maintaining production-grade data pipelines and workflows in live customer environments.Technical Skills:Strong programming skills in Python and SQL.Experience with REST APIs and integration troubleshooting.Familiarity with cloud platforms (e.g., Azure, GCP) and Kubernetes.Knowledge of CI/CD tools and practices for pipeline automation.Experience with Grafana, Power BI, or GraphQL is a plus.Domain Knowledge:Familiarity with industrial data systems or domains such as Oil & Gas, Power, or Manufacturing is a plus.Problem-Solving & Troubleshooting:Strong problem-solving skills with the ability to analyze and troubleshoot complex issues across distributed systems.Communication & Customer-Centric Mindset:Excellent English communication skills (both written and verbal).Customer-first mindset with an ability to work closely with customers to understand and resolve technical issues. Key ResponsibilitiesTroubleshooting Issues & Customer Support:Investigate and debug complex customer-reported issues related to data pipelines, integrations, data models, and Cognite Data Fusion (CDF) functionality.Work with customer teams to understand production incidents, reproduce issues, and implement fixes or workarounds.Analyze data failures, system errors, and unexpected behaviors across API integrations, custom code, and third-party data sources.Proactively identify bottlenecks, configuration mismatches, or anomalies to improve data pipeline reliability and performance.Collaborate with engineering and product teams to escalate platform issues and contribute to long-term resolutions.Advanced and Enterprise-Level Support:Serve as the technical point of contact for high-priority customer support cases.Perform in-depth troubleshooting and diagnostics, including custom code reviews and integration issues with third-party data sources.Engage in regular case reviews, root cause analysis, and progress updates aligned with customer SLAs.Participate in on-call rotations to ensure 24/7 coverage and quick resolution of critical issues.Implement proactive monitoring and alerting systems to identify and address potential issues before they escalate.Customer Enablement & Knowledge Sharing:Develop clear documentation, how-to guides, and knowledge base articles to improve issue resolution efficiency and reduce repeat tickets.Work closely with internal product and engineering teams to relay customer feedback and prioritize product improvements.Required Qualifications & SkillsExperience:3+ years in a data-intensive, customer-facing role, with experience in technical support in a SaaS or data platform environment, ideally in a Tier 2/3 or engineering-focused support function.Proven experience maintaining production-grade data pipelines and workflows in live customer environments.Technical Skills:Strong programming skills in Python and SQL.Experience with REST APIs and integration troubleshooting.Familiarity with cloud platforms (e.g., Azure, GCP) and Kubernetes.Knowledge of CI/CD tools and practices for pipeline automation.Experience with Grafana, Power BI, or GraphQL is a plus.Domain Knowledge:Familiarity with industrial data systems or domains such as Oil & Gas, Power,
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