Senior Forward Deployed Engineer
Build and productionize customer-facing data and AI solutions on the Databricks platform, owning architecture and end-to-end delivery. The role requires 6+ years of software or data engineering experience, cloud expertise, distributed computing knowledge, and strong enterprise customer engagement skills.
About the job
Responsibilities
- Lead customer technical projects by designing and delivering production-grade systems, reference architectures, custom applications, data ingestion, and ML/AI model integrations.
- Guide strategic customers through end-to-end design, development, deployment, evaluation, and adoption of data and AI applications.
- Own architecture and design decisions, ensuring solutions are secure, scalable, performant, and aligned with customer needs and Databricks best practices.
- Collaborate with engagement managers, project managers, architects, Databricks technical teams, engineering, customer support, and customer stakeholders to deliver technical components and resolve issues.
- Embed with customer teams, engage stakeholders from technical contributors through executives, and translate complex challenges into actionable solutions.
- Contribute reusable accelerators, frameworks, documentation, and best practices that scale across accounts and inform the product roadmap.
- Travel to customers approximately 20% of the time.
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 and use modern frameworks.
- Working knowledge of at least two 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 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 working with enterprise clients and managing conflicts across broad stakeholder groups.
- Curiosity, adaptability, and eagerness to explore technologies that support Databricks-based solution deployment and integration.
- Databricks certification.
Compensation
- Base salary range: $182,000–$250,208 USD.
- Compensation may also include an annual performance bonus, equity, and benefits.
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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