Sr. Forward Deployed Engineer
Databricks · Singapore · Professional Services Operations · listed June 10, 2026
The shape of it
Seniority
Senior
Where
Not stated
Requirements listed
6
Length
605 words
In the posting’s own words
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.
What it asks for · 6
- 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.
What the job covers
- 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.
Tools and skills named
Languages
- Java
- JavaScript
- Python
- Scala
- SQL
- TypeScript
Data
- Databricks4×
- Data pipelines
Models & research
- Machine learning3×
Product & design
- Roadmap
Ways of working
- Cross-functional
Words the posting leans on
- customer7×
- engineering6×
- applications5×
- data5×
- design5×
- impact5×
- solutions5×
- deliver3×
- engineers3×
- integration3×
- software3×
- systems3×
- adaptability2×
- architecture lead2×
- backend frontend2×
- challenges2×
Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.
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