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Описание вакансии
Текст:
TL;DR
Sr. Solutions Engineer (Databricks): Leading customer discovery, solution design, proofs of concept, and platform demonstrations across data engineering, analytics, and machine learning with an accent on Python, SQL, cloud architectures, and distributed data systems. Focus on designing production-quality solutions, building live demos, solving technical customer challenges, and presenting Databricks capabilities in competitive evaluations.
Location: Singapore
Company
Databricks is a data and AI company providing a unified platform for data engineering, 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, live demonstrations, notebooks, solution accelerators, and reference architectures on the Databricks Platform.
- Own technical relationships with customer engineers, data teams, and technical leads.
- Develop account-level technical strategies with Account Executives to expand platform consumption.
- Explain Databricks differentiation through hands-on demonstrations and competitive technical evaluations.
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.
- Hands-on 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, discovery sessions, 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.
Culture & Benefits
- Benefits and perks are provided 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 20,000 customer organizations and offices 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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