Lead Support Engineer, Database

PhoenixAI is the Agentic AI Database, purpose-built to give autonomous AI agents sub-second access to live enterprise data at massive scale. The platform unifies real-time and at-rest data in a single AI-native engine, combining the speed and concurrency that agentic workloads demand with the governance and deployment flexibility enterprises require to put AI into production. Formerly known as Celer Data, PhoenixAI is headquartered in Menlo Park, California.

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We’re seeking a Principal or Lead Support Engineer to deliver exceptional technical assistance to PhoenixAI customers, resolving issues, optimizing performance, and driving customer success. This role combines deep technical expertise with a customer-first mindset to troubleshoot, educate, and influence product improvements based on real-world usage.

As a Principal / Lead Support Engineer, you’ll ensure customers maximize PhoenixAI ’s value by resolving technical challenges and enhancing their experience. Your responsibilities include:

• Go-live Support: Collaborate with customers to ensure successful deployment of their projects into production and help them quickly realize the value of PhoenixAI product.
• Issue Resolution: Diagnose and resolve customer issues—ranging from query performance bottlenecks to integration challenges— when using PhoenixAI ’s products.
• Technical Guidance: Provide actionable advice to customers on optimizing PhoenixAI deployments, including configuration tuning, data modeling, and integration with tools like Apache Kafka or BI platforms.
• Case Documentation: Maintain detailed records of support cases—capturing use cases, technical issues, and resolutions—to improve support processes and inform product enhancements.
• Customer Escalation Handling: Act as a point of escalation for complex issues, collaborating with engineering teams to deliver timely, effective solutions under SLAs.
• Feedback Loop: Gather customer feedback and usage insights, partnering with product and engineering teams to refine PhoenixAI ’s capabilities and address recurring pain points.
• Knowledge Sharing: Create and update support resources—like troubleshooting guides, FAQs, and best-practice articles—to empower customers and streamline issue resolution.
• Mentoring and
  
  Coaching:
  
  fostering team members’ technical growth through knowledge sharing, code reviews, and hands‑on guidance. Conduct regular team training sessions and performance feedback to elevate overall support quality.
• Process Improvement: Analyze support trends and metrics to identify opportunities for process enhancements and proactive customer outreach.

• Ambition & Curiosity: A driven, inquisitive mindset—eager to learn PhoenixAI product’s intricacies, tackle tough challenges, and grow into the role, even if starting with less experience or specific skills.
• Experience: 10+ years in a technical support, customer success, or engineering role, ideally with data analytics or database technologies.
• Technical Expertise: Experience with analytical databases (e.g., PhoenixAI /Star Rocks, Click House, Snowflake, Databricks) and strong SQL skills. Ability to troubleshoot issues in a Linux environment across multiple layers (e.g., network, storage, security). Ability to troubleshoot issues in OLAP systems (e.g., query performance, data ingestion). Familiarity with distributed systems, cloud platforms (AWS, GCP, Azure), and data tools (e.g., Kafka, Flink, Tableau).
• Communication
  
  Skills:
  
  Proven ability to communicate technical solutions clearly to diverse audiences, from data engineers to IT managers.
• Problem-Solving: Adept at diagnosing complex issues under pressure and delivering root‑cause resolutions.
• Collaboration: Experience working with engineering teams to elevate product development through issue resolution.
• Leadership: Proven track record of mentoring or leading junior engineers, with a player‑coach mindset—balancing direct technical work with team development.
• Processes: Experience improving support processes, such as implementing SLAs, automation tools, or CI/CD pipelines for issue resolution.
• Bonus Points: Scripting skills (e.g., Python, Bash) for automation or diagnostics. Familiar with real‑time analytics or BI technologies.