Want to get hired at Databricks?
Solutions Architect - Startups
Databricks
HybridHybrid
Original Job Summary
Overview
At Databricks, our customers challenge us to solve some of the world's toughest data problems. As a Solutions Architect - Startups, you will understand the technologies powering our platform and integrate cloud solutions to deliver business value.
Role Responsibilities
- Provide technical leadership and consult on big data architectures.
- Develop and present reference architectures, technical guides, and demo applications.
- Support strategic customer projects with proof of concepts.
- Evangelize open-source projects like Apache Spark, Delta Lake, and MLflow.
- Travel up to 30% locally to customer sites.
What You Will Do
You will design distributed data systems, program in languages such as Python, Scala, Java, SQL, or R, and build solutions using AWS, Azure, or GCP. You will also work on data engineering, data science, and machine learning projects, engaging directly with customers and cross-functional teams.
What We Look For
- 3+ years in a customer-facing technical role.
- Proven experience in designing cloud-based distributed systems.
- Hands-on programming skills in at least one major language.
- Experience with cloud providers and data technology stacks.
- [Preferred] Degree in a quantitative discipline and Databricks Certification.
Key Skills/Competency
- Databricks
- Architecture
- Cloud
- Data Engineering
- Machine Learning
- Apache Spark
- Delta Lake
- MLflow
- Pre-sales
- Customer Support
How to Get Hired at Databricks
🎯 Tips for Getting Hired
- Customize your resume: Highlight cloud and data engineering skills.
- Research Databricks culture: Understand its data and AI focus.
- Prepare for technical interviews: Review distributed systems and programming.
- Showcase customer experience: Emphasize pre-sales and consulting roles.
📝 Interview Preparation Advice
Technical Preparation
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Review cloud platform configuration basics.
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Practice coding in Python or Scala.
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Study distributed systems design patterns.
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Analyze open-source data frameworks.
Behavioral Questions
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Explain a time you led a project.
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Describe customer engagement success stories.
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Discuss handling technical disagreements.
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Share feedback received from team collaborations.