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Solutions Architect - Emerging Enterprise (Startups) Databricks · United States
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Databricks

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Solutions Architect - Emerging Enterprise (Startups)

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🗓️ Posted 2026-08-18 United States Hybrid ICT
💰 Salary Not shared 📊 Market ₹14,000–₹22,000/mo

About the Company

At Databricks, our customers challenge us with solving some of the world's toughest data problems. Our Solutions Architect team understands the technologies that power our platform, the broader cloud and technology ecosystems, and how they can all be brought together to solve these problems. Databricks' culture thrives on collaboration and teamwork.

Responsibilities

  • ● Provide technical leadership for customers to evaluate and adopt Data and AI solutions from Databricks
  • ● Consult on big data architecture, implement proof of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications
  • ● Build and present reference architectures, technical guides, and demo applications for customers
  • ● Provide escalated support for critical customer operational issues
  • ● Become an expert in, and evangelize Databricks driven open-source projects (Apache Spark , Delta Lake, MLflow, Koalas) across developer communities through meetups, conferences, and webinars
  • ● Use your strengths to help your fellow SAs and drive cross-functional relationships across the company
  • ● Travel to customers (up to 30%, of which 80%+ local to your region)

Requirements

  • ● Comfortable communicating ideas to various audiences through presentations, whiteboarding, architecture discussions, and platform demonstrations
  • ● 5+ years in a customer-facing pre-sales, technical architecture, or consulting role
  • ● Experience designing and architecting distributed data systems
  • ● Comfortable programming in and debugging at least one of Python, Scala, Java, SQL, or R
  • ● Have built solutions with public cloud providers, such as AWS, Azure, or GCP
  • ● Experience in at least one of the following: Data Engineering technologies (e.g., Spark, Hadoop, Kafka), Data Warehousing (e.g., SQL, OLTP/OLAP/DSS), or Data Science and Machine Learning technologies (e.g., pandas, scikit-learn, HPO)
  • ● Preferred Degree in a quantitative discipline (e.g., Computer Science, Applied Mathematics, Operations Research, etc.)