Description
As a Sr. Solutions Engineer at Databricks, you will lead the growth of the Databricks Unified Analytics Platform. You will exercise and develop expertise in cloud platforms, data engineering, data analytics, and data science and machine learning. You will work with customers, your teammates, the product team, and our post-sales teams to identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through the implementation to accomplish value.
Your responsibilities will include:
Partnering with the sales team to help customers understand how Databricks can help solve their business problems Providing technical leadership for customers to evaluate and adopt Databricks Consulting on big data architecture, implementing proof of concepts for strategic customer projects, data science and machine learning projects, and validating integrations with cloud services and other 3rd party applications Building and presenting reference architectures, how-tos, and demo applications for customers Becoming an expert in, and promoting Databricks-inspired open-source projects (Apache Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars Traveling to customers in your region
To succeed in this role, you will need:
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 Experience supporting Public Sector clients Have built solutions with public cloud providers such as AWS, Azure, or GCP Expertise in at least one of the following: Data Engineering technologies (Ex: Spark, Hadoop, Kafka), Data Warehousing (Ex: SQL, OLTP/OLAP/DSS), Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, HPO) Secret security clearance or willingness to obtain one