Solutions Architect - Emerging Enterprise (Startups)
Leads technical adoption of Databricks platform for emerging enterprise customers, designs data/AI architectures, builds proofs of concept, and evangelizes open-source projects like Spark and Delta Lake. Requires 5+ years customer-facing experience in data engineering/science and cloud platforms.
About the job
The impact you will have:
- 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 SA's, and drive cross-functional relationships across the company
- Travel to customers (up to 30%, of which 80%+ local to your region)
What we look for:
Solution Architects are customer-facing. You'll need to be 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)
- 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.)
- Nice to have: Databricks Certification
Skills
Spark, Delta Lake, MLflow, Python, Scala, Java, SQL, AWS, Azure, GCP, Hadoop, Kafka, pandas, scikit-learn
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