Senior Data Engineer-Support

Key Responsibilities

• Troubleshooting 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 & Skills

• Experience:
• 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.