# Forward Deployed Engineering Manager [Databricks](https://gurify.com/jobs?q=Databricks) · London, United Kingdom · Posted last week Hybrid [Engineering Manager](https://gurify.com/jobs/engineering-manager) [Apply on the original posting → (opens in a new tab)](https://job-boards.greenhouse.io/databricks/jobs/8910850002) ## Job description ### 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. ### Benefits At 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. **Live in Databricks’s hiring system.** Read from the company's own applicant tracking system, not reposted from a job board — so it's a real, open requisition rather than an ad that outlived the role. 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Handles delivery across direct accounts and navigates technical and scoping alignment with Engagement Managers and client stakeholders.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EFocuses 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.\u003C/li\u003E\u003C/ul\u003E\u003Ch3\u003EKey Responsibilities \u0026amp; Core Behaviors\u003C/h3\u003E\u003Cul\u003E\u003Cli\u003EConnect your team\u2019s 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.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EReinforce your team\u2019s top delivery priorities. 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Run consistent inspection rhythms (standups, project reviews, retrospectives) and hold teammates strictly accountable to timelines and quality bars.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003ETranslate Databricks\u2019 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.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EApply 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). 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