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Описание вакансии
Текст:
TL;DR
Solutions Architect (Data & AI): Leading end-to-end technical strategy for customer accounts and designing scalable production solutions across data engineering, ML/AI, real-time analytics, and cloud-native platforms with an accent on architecture leadership, platform adoption, and technical specialization. Focus on designing distributed data systems, building custom solutions for competitive scenarios, orchestrating cross-functional resources, and translating complex architectures into business value.
Location: London, United Kingdom
Company
Databricks is a Data and AI company providing a unified platform for data engineering, machine learning, analytics, lakehouse workloads, and AI applications.
What you will do
- Own the end-to-end technical strategy for customer accounts, from discovery through production deployment and consumption growth.
- Lead architecture discussions and design scalable, production-grade solutions across data engineering, ML/AI, and real-time analytics.
- Advise customer architects, engineering leads, and directors on technical strategy and platform adoption.
- Build custom solutions for competitive scenarios and demonstrate the Databricks platform's differentiation.
- Develop a technical specialization and coordinate DSAs, SSAs, and partners to solve complex customer needs.
- Provide structured feedback on customer requirements and competitive gaps to influence product direction.
Requirements
- 6+ years of experience in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role.
- Strong Python and SQL skills, including live coding, debugging, and solution building.
- Deep expertise in distributed data systems, scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms.
- Experience with Databricks or the ability to become proficient rapidly, with a developing specialization in areas such as streaming, ML/AI, governance, or migrations.
- Experience leading architecture discussions with senior technical stakeholders and deploying solutions on AWS, Azure, or GCP.
- Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline, or equivalent experience.
Nice to have
- Databricks certifications in data engineering, machine learning, or platform technologies.
- Experience with Snowflake, AWS native services, or Azure Synapse.
- Background in a data/AI company or cloud provider.
- Industry expertise in financial services, healthcare, retail, media, or another relevant sector.
Culture & Benefits
- Comprehensive benefits and perks are offered according to the employee's region.
- Inclusive workplace with equal employment opportunity standards.
- Access to a global organization with offices around the world.
Hiring process
- Recruiter screen and hiring manager screen.
- Design and architecture interview followed by a live coding assessment.
- Build, Demo, Pitch! presentation and reference check.
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