Forward Deployed Engineering Manager

About the role

Req ID: CSQ128R179

Location: London, United Kingdom - Hybrid

Recruiter: Dina Hussain

Role Overview

As a Forward Deployed Engineering (FDE) Manager, you will lead a high-performing delivery team of 8+ Individual Contributors (ICs) to build and productionize solutions for customers' data and AI challenges using the Databricks platform. You are responsible for ensuring high-quality technical execution, driving professional services business outcomes, and nurturing elite engineering talent while remaining close to the technology and execution.

Scope of Impact & Leveling Criteria

- Oversees successful delivery at the delivery team and account level, driving Professional Services (PS) business outcomes through high-quality execution. Impact is measured by key metrics including Bookings, Revenue, Margin, CSAT, and Direct Consumption / Delta Cloud Consumption (DBUs).

- Typically manages an elite engineering team of 8+ Individual Contributors. Handles delivery across direct accounts and navigates technical and scoping alignment with Engagement Managers and client stakeholders.

- Focuses internally on building team capabilities and externally on account execution. Mandates high standards for Greenhouse scorecards and interview calibrations, ensuring clear pass/fail hiring signals.

Key Responsibilities & Core Behaviors

- Connect your team’s day-to-day work to real customer outcomes and business impact. Build excitement about Databricks by sharing customer wins and delivery successes, making each individual feel motivated and appreciated.

- Reinforce your team’s top delivery priorities. Help your team focus on high-impact technical work, redirecting effort away from low-value tasks and removing blockers that slow execution. Use delivery data and PS KPIs to confirm focus areas.

- Hire strong PS talent using structured interviews and practical delivery scenarios. Ensure team takes 2–4 protected hours a week for continuous technical learning and experimentation. Understand your team’s strengths and growth areas to provide regular coaching, and handle underperformance early with clear feedback and accountability.

- Remove delivery blockers quickly, using simple automation or AI assistants to accelerate routine work. Run consistent inspection rhythms (standups, project reviews, retrospectives) and hold teammates strictly accountable to timelines and quality bars.

- Translate Databricks’ Culture Principles (Customer Obsessed, Truth Seeking, First Principles, Raise the Bar, Company-First, Bias for Action) into concrete day-to-day behaviors, ensuring standards are upheld in all customer interactions.

- Apply a builder and AI-first mindset to improve team productivity. Review delivery plans and architectures utilizing practical knowledge of the Databricks platform and cloud environments (AWS, Azure, GCP). Actively coach ICs on secure, scalable deployment patterns, governance, and production readiness.