Forward Deployed Engineer
Delivers production-grade data and AI solutions for enterprise customers using the Databricks platform, owning architecture, implementation, and customer adoption. The role requires strong data or software engineering experience, cloud expertise, Apache Spark, MLOps, and technical project delivery skills.
About the job
Responsibilities
- Lead impactful 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.
- Guide customers on architecture and design, and bootstrap or implement projects that support successful Databricks evaluation and adoption.
- Own architecture and design decisions, ensuring solutions are secure, scalable, and aligned with customer needs and Databricks best practices.
- Collaborate with Databricks technical teams, project managers, architects, and customer teams to deliver engagement components.
- Work with Engineering and Customer Support to provide product and implementation feedback and resolve engagement-specific 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 influence the Databricks product roadmap.
- Travel to customers approximately 20% of the time.
Requirements
- Extensive experience in data engineering, data platforms and analytics, or software engineering.
- Ability to write code in Python, Scala, JavaScript/TypeScript, and modern frameworks.
- Working knowledge of at least two major cloud ecosystems, with expertise in one: AWS, Azure, or Google Cloud.
- 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, machine learning and artificial intelligence 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, including managing scope, timelines, measurable outcomes, and translating complex concepts into actionable solutions.
- Documentation and whiteboarding skills.
- Experience working with enterprise clients and managing conflicts across broad stakeholder groups.
- Curiosity, adaptability, and eagerness to explore technologies supporting Databricks-based solution deployment and integration.
Nice to have
- Databricks Certification.
Skills
Python, Scala, JavaScript, TypeScript, AWS, Microsoft Azure, GCP, Spark, CI/CD, MLOps, Machine Learning, Artificial Intelligence, Ai Apis, Data Engineering, Databricks
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