Global Field Engineering Manager - Data & AI Solutions

Databricks; United Kingdom; Remote; GBP 130,000 - 179,000; Full time

Job summary

Databricks is seeking a Manager, Field Engineering to lead a team of technical customer advisors solving complex data, analytics, and AI challenges. You will align with Sales and cross-functional partners to translate customer priorities into effective technical strategies and durable business impact.

You will manage a team of ~8–10 professionals, coaching and building collaboration practices to ensure success while maintaining technical credibility across Databricks platform concepts and cloud

Qualifications

• Experience leading technical customer-facing professionals in enterprise software, cloud, data, AI, analytics or related consulting.
• Proven ability to hire, coach, motivate and retain technical talent.
• Strong feedback, career conversations, and performance issue handling.

Responsibilities

• Lead, coach, and develop a high-performing Field Engineering team.
• Define technical-win strategy with account teams and prioritize customer needs.
• Build trusted relationships with Director-, Head of-, and VP-level stakeholders.
• Guide discovery, solution strategy, architecture discussions, adoption planning, and value realization.
• Establish operating rhythms to inspect progress, health, risk, escalations, capacity, and impact.

Skills

Leadership

Customer advisory

Stakeholder management

Technical storytelling

Data platforms

Education

Bachelor's degree in CS/IS/Engineering or equivalent

Tools

Databricks

Job description

Databricks is seeking a Manager, Field Engineering to lead a team of technical customer advisors solving complex data, analytics, and AI challenges. You will align with Sales and cross-functional partners to translate customer priorities into effective technical strategies and durable business impact.

You will manage a team of ~8–10 professionals, coaching and building collaboration practices to ensure success while maintaining technical credibility across Databricks platform concepts and cloud