Forward Deployed Engineer
Build and productionize customer-facing data and AI solutions on the Databricks platform, owning architecture, implementation, and technical delivery. Requires 6+ years of engineering experience, cloud expertise, Apache Spark, ML/AI, and enterprise client engagement skills.
About the job
Responsibilities
- Lead customer technical projects by delivering production-grade systems, reference architectures, custom applications, data ingestion, and ML/AI model integrations.
- Guide strategic customers through the end-to-end design, build, and deployment of big data and AI applications.
- Scope technical delivery work with engagement managers and customer input.
- Advise customers on architecture and design, and bootstrap or implement projects to support successful Databricks adoption.
- Own architecture and design decisions, ensuring solutions are secure, scalable, and aligned with customer needs and Databricks best practices.
- Coordinate with Databricks technical teams, project managers, architects, and customer teams to deliver technical engagement components.
- Provide product and implementation feedback and help resolve engagement-specific product and support issues.
- Embed with customer teams and engage stakeholders ranging from technical individual contributors to executives.
- Contribute accelerators, frameworks, and best practices that scale impact across accounts and inform the Databricks product roadmap.
Requirements
- 6+ years of experience in data engineering, data platforms and analytics, or software engineering.
- Ability to write code in Python, Scala, JavaScript, or TypeScript using modern frameworks.
- Working knowledge of at least two cloud ecosystems among AWS, Azure, and Google Cloud, with expertise in at least one.
- Deep experience with distributed computing using 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.
- Experience designing and deploying performant, production-grade end-to-end data architectures and applications combining data pipelines, ML/AI models, and user-facing interfaces.
- Experience delivering technical projects, managing scope and timelines, measuring outcomes, and translating complex concepts into actionable solutions.
- Documentation and whiteboarding skills.
- Experience with enterprise clients and managing conflicts across broad stakeholder groups.
- Curiosity, adaptability, and eagerness to learn technologies supporting Databricks-based solution deployment and integration.
- Willingness to travel to customers 20% of the time.
- Databricks certification.
Benefits
- Comprehensive benefits and perks are offered, with details varying by region.
Skills
Python, Scala, JavaScript, TypeScript, AWS, Azure, GCP, Spark, CI/CD, MLOps, Machine Learning, Ai Apis, Data Pipelines, Data Architecture, Databricks
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