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Forward Deployed Engineering Manager

London, United KingdomHybridSeniorFull-time

Posted yesterday

The role in short

Lead a team of forward-deployed engineers to build and productionize data and AI solutions for customers using the Databricks platform.

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.

What We Look For

  • Experience: 8+ years of total technical experience with 2+ years of experience managing, leading, or mentoring high-caliber technical teams in data engineering, data platforms, software engineering, or AI/ML.
  • Technical Depth: Strong technical background capable of evaluating architectures spanning distributed computing (Apache Spark™), Python/Scala, modern cloud ecosystems (AWS, Azure, GCP), CI/CD, and MLOps/GenAI frameworks.
  • Leadership Skills: Proven ability to manage technical project delivery, timelines, scoping, conflict resolution, and executive customer relationships from technical ICs up to Director level.
  • Certifications: Databricks Certification required (or path to completion).

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

BenefitsAt Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Prep for this interview

2 questions likely to come up at Databricks, each matched to a line in this posting.

  1. 1Cloud, deployment and security
    They wrote: “Technical Depth: Strong technical background capable of evaluating architectures spanning distributed computing (Apache Spark™), Python/Scala, modern cloud ecosystems (AWS, Azure, GCP), CI/CD, and MLOps/GenAI frameworks.”

    How would you debug a deployment that works in staging but fails at the customer's site?

    How to answer

    Why they ask: Customer environments differ in ways you can't see. This tests method under pressure.

    1. Compare versions, config and environment variables
    2. Check network rules, proxies and certificates (common in enterprise)
    3. Look at resource limits and permissions
    4. Add the missing check to your install steps afterwards

    Tip: List the usual suspects and how you'd check each without full access.

  2. 2Discovery and scoping
    They wrote: “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.”

    How do you decide what to build first when a customer wants ten things?

    How to answer

    Why they ask: FDEs have limited weeks per customer. This tests judgment about value, effort and risk.

    1. Score each request by business value and by effort, with the customer in the room
    2. Pick one item that proves value fast and unblocks later work
    3. Write down what's out of scope so it doesn't creep back in
    4. Revisit the list after the first release, with real usage data

    Tip: Show a simple way to rank the list and name what you'd leave out on purpose.

All FDE interview questions, by what postings ask for

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