Databricks3 дня назад

Архитектор решений - CPG и производство

Зарплата не указана

РЫНОК

15 000 ₽медиана по профессии

Solution Architect · 60 вакансий с указанной зарплатой

5 600половина предложений: 15 000–18 258180 000

Работодатель не указал зарплату — сравните с рынком сами.

Zürich

Обязанности

01Own the end-to-end technical strategy for your accounts — from discovery through production deployment — driving competitive wins by building differentiated AI and data solutions that accelerate consumption growth
02Lead complex architecture discussions — designing production-grade solutions across data engineering, AI/ML, agentic systems, and real-time analytics
03Serve as a trusted technical partner to customer architects, engineering leads, and Directors — helping shape their data and AI journey on Databricks
04Develop an emerging technical specialization (archetype) — ideally in AI/ML, agentic architectures, or a related domain — becoming a go-to resource within your team
05Orchestrate cross-functional resources (DSAs, SSAs, Partners) to deliver end-to-end AI and data solutions for complex customer needs
06Provide structured feedback to product teams on customer requirements, AI capabilities, and competitive gaps

016+ years in solutions architecture, data engineering, data science/AI, or technical pre-sales — with a strong track record of hands-on solution building and customer-facing technical leadership
02Deep expertise in modern data and AI architectures — lakehouse design, scalable pipelines, real-time/streaming, and cloud-native platforms
03Strong understanding of AI/ML concepts, agentic architectures, and ontology design — including experience with compound AI systems, autonomous agent frameworks, knowledge graphs, and semantic data models
04Proficient on the Databricks Platform (or demonstrated ability to achieve proficiency rapidly) with a developing technical specialization in one area
05Experience with production deployments on public cloud (AWS, Azure, or GCP), including security and governance considerations
06Track record of driving platform adoption and consumption growth — particularly across AI/ML and data analytics workloads
07Excellent communication skills — able to translate complex AI and data architectures into business value for technical and executive audiences
08Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)