Global Head of Support Engineering

Americas

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$160,000 – $220,000Compensation

Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Data, AI, SaaSIndustries

Requirements

Candidates should have over 5 years of experience in technical support, with at least 2 years in a leadership role managing technical support teams, preferably in a SaaS environment with remote structures. A strong technical background is essential, including comfort with log troubleshooting, database querying, APIs, and debugging tools like Postman and SQL. Proven success in building scalable support processes and KPIs, exceptional communication skills, and a customer-first mindset are required. Experience with support systems like Zendesk, documentation tools like Notion, and CRM systems is preferred, as is familiarity with data infrastructure or observability products.

Responsibilities

The Global Head of Support Engineering will lead, mentor, and develop the global Technical Support Engineering team, fostering technical excellence and customer-focused problem-solving. This role involves defining and optimizing support processes, SLAs, and escalation frameworks, while implementing and monitoring KPIs for continuous improvement. The Head will act as the ultimate escalation point for critical customer issues, advocating for customer needs to influence product and engineering decisions. Responsibilities also include collaborating with Product Management, Engineering, Customer Success, and Sales teams, driving automation and tooling improvements for support workflows, and developing the long-term strategy for the Support Engineering function.

Skills

Technical Support

Team Leadership

Process Optimization

Customer Success

SLAs

KPI Monitoring

Escalation Management

Monte Carlo Data

Provides end-to-end data observability solutions

About Monte Carlo Data

Monte Carlo Data helps businesses ensure the reliability of their data through end-to-end data observability, allowing real-time monitoring of data freshness, volume, schema, and quality. Their platform includes tools for incident detection and resolution, which assist analysts in addressing data quality issues efficiently. By integrating with communication tools like Slack and JIRA, it fits seamlessly into existing data management processes. The goal is to help businesses avoid the costs associated with bad data, making it suitable for data-dependent companies across various industries.

San Francisco, CaliforniaHeadquarters

2019Year Founded

$229.6MTotal Funding

SERIES_DCompany Stage

Data & Analytics, AI & Machine LearningIndustries

201-500Employees