Forward Deployed Engineer - Emerging Enterprise & DNB
Delivers and productionizes customer data and AI solutions on the Databricks platform, owning architecture, implementation, and technical project outcomes. The role requires extensive data or software engineering experience, cloud expertise, Apache Spark, CI/CD, and MLOps knowledge, with a customer-facing delivery focus.
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 end-to-end design, development, deployment, and adoption of big data and AI applications.
- Scope technical delivery work with engagement managers and customer stakeholders.
- Guide customers on architecture and design, and bootstrap or implement customer projects.
- 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 Databricks Customer Support to provide product and implementation feedback and resolve engagement-specific issues.
- Embed with customer teams and engage stakeholders from technical individual contributors through executives.
- Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the 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 or more of AWS, Azure, and GCP.
- 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, including managing scope, timelines, and measurable outcomes and translating complex concepts into actionable solutions.
- Documentation and whiteboarding skills.
- Experience working with Emerging Enterprise and Digital Native businesses and managing conflicts across broad stakeholder groups.
- Curiosity, adaptability, and eagerness to explore technologies that support the deployment and integration of Databricks-based solutions.
- Databricks Certification.
Benefits
- Comprehensive benefits and perks are offered, with details varying by region.
Skills
Python, Scala, JavaScript, TypeScript, AWS, Microsoft Azure, GCP, Spark, CI/CD, MLOps, Machine Learning, Ai Apis, Data Engineering, Data Pipelines, Databricks
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