В Databricks предстоит напрямую создавать production-системы для данных и ИИ и отвечать за архитектуру крупных клиентских проектов, но широкий круг задач и поездки к клиентам в 20% случаев важно учитывать.
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Широкая зона ответственностиПоездки к клиентамСовременные технологииСильная продуктовая компанияВлияние на продукт
Оценка от Hirify AI
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Senior Technical Program Manager, FDE - LATAM (Data & AI): Building and productionizing customer-facing data, AI, and application solutions on the Databricks platform with an accent on end-to-end architecture, distributed computing, and production delivery. Focus on designing secure and scalable systems, integrating data pipelines with ML/AI models and user-facing interfaces, and guiding complex enterprise projects to measurable outcomes.
Location: USCA; travel to customers 20% of the time
Company
Databricks is a Data and AI company providing a unified platform for data engineering, analytics, machine learning, and AI application development.
What you will do
Lead customer technical projects by designing and delivering production-grade data platforms, reference architectures, custom applications, data ingestion systems, and ML/AI integrations.
Guide strategic enterprise customers through the end-to-end design, build, deployment, evaluation, and adoption of big data and AI applications.
Own architecture and design decisions, ensuring solutions are secure, scalable, and aligned with customer needs and Databricks best practices.
Embed with customer teams, work with technical and executive stakeholders, provide training, and translate complex challenges into actionable solutions.
Coordinate with Databricks engineering, customer support, project management, architecture, and customer teams to deliver engagements and resolve implementation issues.
Develop reusable accelerators, frameworks, and best practices that scale across accounts and inform the Databricks product roadmap.
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 major cloud ecosystems among AWS, Azure, and GCP, with expertise in at least one.
Deep experience with distributed computing using Apache Spark, including knowledge of Spark runtime internals.
Familiarity with CI/CD for production deployments, MLOps, ML/AI models, and AI APIs.
Experience designing and deploying performant, production-ready 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, plus experience working with enterprise clients and managing conflicts across diverse stakeholders.
Databricks Certification.
Culture & Benefits
Customer-facing, hands-on work at the intersection of technology and business impact.
Cross-functional collaboration with engineering, product, developer relations, project management, architecture, and customer support.
Comprehensive benefits and perks, with details varying by region.
Commitment to an inclusive culture and equal employment opportunity.
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