Closed: Senior Forward Deployed Engineer - Architect

Responsibilities

Build and productionize customer solutions for data and AI challenges using the Databricks platform.
Own architecture and lead design decisions for end-to-end systems spanning data engineering, AI, and application development.
Deliver production-grade systems, reference architectures, custom applications, data ingestion, and ML/AI model integrations.
Guide strategic customers through the design, build, and deployment of big data and AI applications.
Scope technical delivery work with customers and engagement managers, managing project timelines and measurable outcomes.
Advise customers on architecture and design, and support project evaluation and adoption of Databricks.
Ensure solutions are secure, scalable, and aligned with customer needs and Databricks best practices.
Collaborate with Databricks technical teams, project managers, architects, customer teams, engineering, and customer support.
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 across accounts and influence the Databricks product roadmap.
Travel to customers approximately 20% of the time.

Extensive 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 major cloud ecosystems, with expertise in at least 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 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, and translating complex concepts into actionable solutions.
Strong documentation and whiteboarding skills.
Experience working with enterprise clients and managing conflicts across diverse stakeholder groups.
Curiosity, adaptability, and eagerness to explore technologies that support Databricks-based solution deployment and integration.
Databricks certification.