Databricks дает сильный опыт работы с корпоративной инфраструктурой данных и AI, а обязанности описаны подробно и включают актуальные облачные инструменты. При этом широкий набор технических требований, поездки и отсутствие зарплаты затрудняют оценку нагрузки и компенсации.
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Широкий профильЧастые поездкиЗарплата не указанаАктуальный стекСфера AI и данных
Оценка от Hirify AI
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Текст:
Hirify AI/Оригинал
TL;DR
Senior Specialist Solutions Engineer (Infrastructure & Platform) (Databricks/cloud infrastructure): Architecting and securing enterprise Databricks deployments across AWS, Azure, and GCP with an accent on cloud networking, identity management, infrastructure automation, and platform administration. Focus on designing scalable private-connectivity architectures, solving complex security and deployment challenges, and demonstrating custom solutions to enterprise customers.
Location: London, United Kingdom. Willingness to travel up to 30% as needed.
Company
Databricks is a data and AI company providing a unified platform for data engineering, analytics, machine learning, governance, and AI applications.
What you will do
Guide enterprise customers through the full lifecycle of Databricks deployments on AWS, Azure, or GCP, from architecture through production.
Design secure and scalable cloud environments covering networking, private connectivity, identity, encryption, and compliance.
Build and maintain infrastructure automation using Terraform and cloud-native infrastructure-as-code tools.
Support competitive technical engagements through custom-built solutions, workshops, and architecture demonstrations.
Collaborate with DSAs, SAs, FDEs, and partners on complex customer requirements.
Provide structured customer feedback to influence product direction and contribute to field-engineering thought leadership.
Requirements
4+ years of experience in solutions architecture, technical pre-sales, or hands-on network architecture.
Strong expertise in cloud security, identity protocols, enterprise networking, private connectivity, platform administration, observability, and cost management.
Hands-on experience with infrastructure automation and IaC tools, including Terraform and relevant AWS, Azure, or GCP tooling.
Strong coding proficiency in Python and PySpark/Spark, including live coding, debugging, and solution building.
Knowledge of distributed data systems, scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms.
Ability to lead architecture discussions with senior technical stakeholders and communicate complex designs as business value.
Nice to have
Databricks or professional-level AWS, Azure, or Google Cloud certifications.
Experience with Snowflake, cloud-native data services, Azure Synapse, or BigQuery.
Background in a data and AI company or cloud provider.
Culture & Benefits
Comprehensive benefits and perks tailored to the employee's region.
Inclusive workplace focused on equal employment opportunity and diversity.
Opportunity to work with enterprise customers and contribute to technical communities and field-engineering content.
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