Forward Deployed Engineering - Senior Architect
Leads customer-facing architecture, implementation, and production delivery of end-to-end data and AI solutions on the Databricks platform. Requires 6+ years of engineering experience, cloud expertise, Apache Spark, MLOps, and strong enterprise stakeholder-management 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 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; bootstrap or implement projects that support successful understanding, evaluation, and adoption of Databricks.
- 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.
- Partner with Engineering and Customer Support to provide product and implementation feedback and resolve engagement-specific issues.
- Embed with customer teams and engage stakeholders 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
- 6+ years of 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 cloud ecosystems, including 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 supporting Databricks-based solution deployment and integration.
- 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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