Databricks

Builds cloud software for data analysis and AI

Forward Deployed Engineering

Implementation & Technical Account ManagementConfirmed live in the last 24 hours

Full-timeLondon, UKNo salary listed

About the Job

Requirements

Strong experience in data engineering, data platforms and analytics, or software engineering.
Comfort writing code in Python, Scala, JavaScript/TypeScript, and modern frameworks.
Working knowledge of at least two common cloud ecosystems (AWS, Azure, or GCP), with expertise in at least one.
Deep experience with distributed computing using Apache Spark and knowledge of Spark runtime internals.
Familiarity with continuous integration and continuous delivery for production deployments.
Working knowledge of MLOps, machine learning and artificial intelligence models, and AI application programming interfaces.
Experience designing and deploying performant production end-to-end data architectures and applications combining data pipelines, machine learning and artificial intelligence models, and user-facing interfaces.
Experience delivering technical projects, including managing scope, timelines, and measurable outcomes and translating complex concepts into actionable solutions.
Documentation and whiteboarding skills.
Experience working with enterprise clients and managing conflicts across a broad range of stakeholders.
Ability to build skills in technical areas and demonstrate curiosity, adaptability, and eagerness to explore technologies supporting deployment and integration of Databricks-based solutions.
Willingness to travel to customers 20% of the time.

Responsibilities

Lead customer technical projects by delivering production-grade systems, designing and building reference architectures and custom applications, and integrating data ingestion with machine learning and artificial intelligence models.
Guide strategic customers through transformational big data projects, including end-to-end design, build, and deployment of big data and artificial intelligence applications; scope technical delivery work with engagement managers and customer input.
Guide customers on architecture and design, and bootstrap or implement customer projects to support their understanding, evaluation, and adoption of Databricks.
Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with customer needs and Databricks best practices.
Coordinate with the Databricks technical team, project manager, architect, and customer team to deliver technical engagement components that meet customer needs.
Work with Engineering and Databricks Customer Support to provide product and implementation feedback and resolve engagement-specific product and support issues.
Embed with customer teams and engage stakeholders from technical individual contributors to executives to understand challenges and deliver impact.
Contribute accelerators, frameworks, and best practices to scale impact across accounts and influence the Databricks product roadmap.
Work with customers to build and productionize solutions to data and artificial intelligence challenges using the Databricks platform.
Own architecture, lead design decisions, and implement end-to-end systems spanning data engineering, artificial intelligence, and application development.
Work cross-functionally with engineering, product, and developer relations to shape long-term strategic priorities and initiatives.
Integrate with client systems and provide training and other technical support to help customers realize value from their data.
Complete billable customer projects according to specification.

Desired Qualifications

Databricks certification is preferred but not essential.

As a Forward Deployed Engineer (FDE) you will work with customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data.

This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy.

The impact you will have:

Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration
Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer
Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.
Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.
Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.
Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.

What we look for:

- strong experience in data engineering, data platforms & analytics, or software engineering
- Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks
- Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
- Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
- Familiarity with CI/CD for production deployments
- Working knowledge of MLOps, ML/AI models and AI APIs
- Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces.
- Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions.
- Documentation and white-boarding skills.
- Experience working with enterprise clients and managing conflicts across a broad stakeholder range
- Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects.
- Travel to customers 20% of the time
- Databricks Certification preferred but not essential

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.

About the Company

Databricks

Builds cloud software for data analysis and AI

Databricks builds cloud software that businesses use to organize data, analyze it, and develop AI applications. Its lakehouse architecture brings the flexible storage of a data lake together with the querying and management tools of a data warehouse. Data engineers prepare and update datasets, analysts build reports, and developers train models or create applications in a shared workspace with controls over who can use the data. The platform runs on Amazon, Microsoft, and Google clouds, and customers pay for computing usage or commit to longer contracts for discounted rates. Databricks was founded in 2013 and is headquartered in San Francisco, California.

Company size: 10,001+
Company stage: Late Stage VC
Total funding: $32.1B
Headquarters: San Francisco, CA
Founded: 2013

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