Forward Deployed Engineer

Reposted 2 Days Ago
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London, Greater London, England, GBR
In-Office
Entry level
Big Data • Machine Learning • Software • Analytics • Big Data Analytics
The Role
Design and deliver custom, production-grade full-stack applications and data and AI solutions for strategic Databricks customers. Own architecture, develop backend and frontend systems, integrate data pipelines and AI models, collaborate with customer stakeholders and internal teams, and create reusable accelerators. The role requires strong software engineering across multiple languages and technologies, customer-facing communication, adaptability, and travel to client sites up to 50% of the time.
Summary Generated by Built In

About the Team

The Forward Deployed Engineering (FDE) team is a highly specialized, customer-facing software engineering team at Databricks. We work with Databricks most strategic customers to design, build, and productionize first-of-their-kind data and AI solutions.  This team is the right fit for you if you love working side-by-side with customers, collaborating with teammates, and pushing your curiosity across the latest trends in data, applications, and AI innovation.

Role Description

As a Forward Deployed Engineer (FDE), you will embed directly with our most strategic customers to design and deliver custom fullstack applications and solutions on the Databricks Data Intelligence Platform and other common software stacks. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development.

This is a hands-on, customer-facing role for software engineers, developers, and builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for solving complex problems that drive measurable outcomes.

The impact you will have:

  • Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.
  • Application Engineering: Design and develop applications spanning backend, frontend, and integrations, bringing data and AI to life for enterprise users leveraging the Databricks platform. 
  • Solution Delivery: Deliver production-grade systems from data ingestion and transformation through ML/AI model integration to user-facing applications and enablement.
  • Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.
  • Cross-Functional Collaboration: Partner with Sales, Product, and Field Engineering to ensure a seamless customer journey from pre-sales through post-deployment.
  • Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.

What we look for:

  • Engineering Depth: Strong background in software engineering with experience across backend, frontend, and systems integration. Proficiency in Python, SQL, Java/Scala, JavaScript/TypeScript, and modern frameworks.
  • Application Delivery: Demonstrated ability to design, build, and deploy production applications that combine data pipelines, ML/AI models, and user-facing interfaces.
  • AI/ML Experience: Familiarity working with AI APIs such as OpenAI, Anthropic, and Gemini into applications, and leveraging AI code generation tools to accelerate productivity. 
  • Customer Impact: Proven track record of delivering technical solutions in enterprise environments that drive measurable outcomes.
  • Collaboration & Communication: Ability to engage across a broad stakeholder range, from engineers to C-level executives, translating complex concepts into actionable solutions.
  • Learning Mindset: Curiosity, adaptability, and eagerness to explore new technologies, domains, and customer challenges.
  • Ability and interest to travel up to 50% as needed to client sites.

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.

Skills Required

  • Strong software engineering experience across backend, frontend, and systems integration
  • Proficiency in Python, SQL, Java or Scala, JavaScript or TypeScript, and modern frameworks
  • Experience designing, building, and deploying production applications combining data pipelines, ML or AI models, and user-facing interfaces
  • Familiarity integrating AI APIs such as OpenAI, Anthropic, and Gemini into applications
  • Experience delivering technical solutions in enterprise environments with measurable outcomes
  • Ability to engage with engineers, technical stakeholders, and C-level executives and translate complex concepts into actionable solutions
  • Curiosity, adaptability, and willingness to learn new technologies, domains, and customer challenges
  • Ability and interest to travel up to 50% to client sites

Databricks Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.

  • Healthcare Strength — Company materials highlight comprehensive medical, dental, and vision coverage alongside mental-health resources, wellness reimbursements, and business travel insurance. Offerings are described as broad and modern, with core health coverage consistently emphasized.
  • Parental & Family Support — Paid parental leave is explicitly called out, with details such as up to 20 weeks for birthing parents and up to 12 weeks for non-birthing parents in the U.S. Public materials also reference family-forming support, reinforcing the focus on families.
  • Wellbeing & Lifestyle Benefits — Wellness programs and perks include gym reimbursement, periodic wellness events (e.g., yoga, massages), and in-office meals and snacks in many locations. Personal development funds and discounts further enhance lifestyle and growth support.

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The Company
HQ: San Francisco, CA
2,200 Employees
Year Founded: 2013

What We Do

As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.

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