Technical Support Manager - Hadoop Observability & Open Data Platform

Leadership & Team Management

Lead and develop a globally distributed technical support team in a 24/7/365 environment. Provide structured coaching through 1:1s, case reviews, and enablement, integrating AI-assisted insights into reviews while ensuring outputs are validated to drive technically grounded responses, consistent case progression, and empathetic customer communication.

Oversee hiring, onboarding, and professional development across locations, building strong skills in technical troubleshooting, customer communication, and effective use of AI tools in support workflows. Ensure employees have clear career pathways that recognize technical excellence, customer impact, and AI-augmented performance.

Lead with clear context and a global mindset, delegating effectively to drive ownership and accountability, removing barriers, and keeping teams focused on shared goals connected to business outcomes.

Operational Excellence & AI-Driven Insights

Maintain end-to-end ownership of customer incidents and model high-quality case handling by leading from the front on critical escalations, blending deep technical reasoning with AI tools to accelerate diagnosis while maintaining accuracy and customer trust.

Use data-driven and AI-assisted strategies to optimise efficiency. Monitor KPIs (case ownership, backlog, response times, resolution SLAs) and translate insights into clear, actionable plans for the team.

Ensure responsible AI use by setting standards for validating outputs before they reach customers, defining guardrails for privacy, security, and data use, and reviewing AI-related metrics (adoption, quality, error rates).

Cross-Functional Collaboration

Build strong partnerships with Product, Engineering, Sales, Professional Services, and internal AI/platform teams to ensure Support's needs are represented in product and tooling decisions.

Collaborate with escalation management and partner teams to resolve complex issues, using operational and AI-generated insights to identify patterns and address root causes.

Drive knowledge sharing and AI enablement by encouraging AI-assisted co-authoring of knowledge content, and transform customer feedback into actionable service improvements, including opportunities to refine support tooling and AI models.

Change Management & AI-Driven Innovation

Identify operational gaps and partner with cross-functional teams to improve case-handling frameworks, tooling, and training resources, including AI assistants embedded in support workflows.

Champion organisational change and the scaling of new AI capabilities. Engage constructively in discussions, align on decisions, and execute. Lead pilots and rollout plans for new tools, defining success metrics, monitoring impact, and ensuring sustainable adoption.

Foster a collaborative culture of excellence and experimentation, where engineers and managers are encouraged to propose, test, and measure AI-driven improvements to how they work.