Forward Deployed Engineer
Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.
Funding history
Investors
About Databricks
Data engineers, analysts, and AI teams use Databricks to process large datasets, build reliable pipelines, and train models on a single governed platform. Users can run SQL analytics, serve ML predictions in real time, and deploy AI agents grounded in enterprise data. Its open lakehouse architecture provides consistent security and governance across analytical and operational workloads.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will build and productionize end-to-end data, AI, and application solutions for customers. You will lead architecture and design decisions, deliver technical projects, guide adoption, resolve implementation issues, and create reusable accelerators and best practices.
Requirements
- 9+ years of experience in data engineering, data platforms and analytics, or software engineering.
- Proficiency in Python, Scala, JavaScript, or TypeScript.
- Knowledge of at least two cloud ecosystems, including AWS, Azure, or GCP.
- Deep experience with Apache Spark and Spark runtime internals.
- Familiarity with CI/CD for production deployments.
- Knowledge of MLOps, ML/AI models, and AI APIs.
- Experience designing and deploying end-to-end data architectures and applications.
- Technical project delivery experience.
- Documentation and whiteboarding skills.
- Enterprise client and stakeholder-management experience.
- Databricks Certification.
- Ability to travel to customers 20% of the time.
Responsibilities
- Lead customer technical projects and deliver production-grade systems.
- Design and build reference architectures, custom applications, data ingestion, and ML/AI model integrations.
- Guide customers through the design, build, and deployment of big data and AI applications.
- Lead architecture and design decisions for secure, scalable solutions.
- Coordinate technical engagement components with project managers, architects, and customer teams.
- Provide product and implementation feedback and help resolve product and support issues.
- Embed with customer teams to understand challenges and deliver impact.
- Contribute reusable accelerators, frameworks, and best practices.
