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Описание вакансии
Текст:
TL;DR
Senior Solutions Engineer (Data & AI): Leading technical discovery, solution design, proofs of concept, and live demonstrations for customer workloads across data engineering, analytics, and machine learning with an accent on Python, SQL, cloud platforms, and distributed data systems. Focus on designing production-quality data solutions, building technical assets, presenting competitive platform differentiators, and solving customer architecture challenges.
Location: London, United Kingdom
Company
Databricks provides a unified Data and AI Platform for building and scaling data, analytics, machine learning, and AI applications.
What you will do
- Lead technical discovery and solution design for customer workloads across data engineering, analytics, and machine learning.
- Build and deliver proofs of concept and live demonstrations on the Databricks Platform.
- Own technical relationships with customer engineers, data teams, and technical leads.
- Develop account-level technical strategies with the Account Executive to expand platform usage.
- Explain Databricks differentiation through hands-on demonstrations and competitive positioning.
- Create reusable notebooks, solution accelerators, and reference architectures for the Solutions Architect community.
Requirements
- 4+ years of experience in data engineering, solutions architecture, technical pre-sales, or hands-on consulting.
- Proficiency in Python and SQL, including debugging, optimization, and production-quality coding; live coding is required during the interview.
- Experience designing and implementing data solutions on AWS, Azure, or GCP.
- Working knowledge of distributed data systems such as Apache Spark, Delta Lake, Hadoop, Kafka, or Flink.
- Experience leading technical customer conversations, including discovery, whiteboarding, and architecture reviews.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a quantitative discipline, or equivalent experience.
Nice to have
- Databricks certification or experience with the Databricks Platform.
- Experience with Unity Catalog, Lakeflow Spark Declarative Pipelines, or MLflow.
- Background at a data or AI company, cloud provider, or technical consulting firm.
- Experience with ETL/ELT, medallion architecture, streaming, model training, MLOps, or SQL analytics.
Culture & Benefits
- Comprehensive benefits and perks are offered according to the employee’s region.
- Inclusive hiring practices and a commitment to diversity and equal employment opportunity.
- Access to a global organization with more than 30 offices and customers worldwide.
Hiring process
- Recruiter screen followed by a hiring manager screen.
- Design and architecture interview, live coding assessment, and build-demo-pitch presentation.
- Reference check.
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