Description
As a Sr. Solutions Engineer at Databricks, you will lead the growth of the Databricks Unified Analytics Platform. This is a customer-facing role, where 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.
In that process, you will build relationships with our customers, find and build champions, and become a trusted advisor. You will partner with the sales team to help customers understand how Databricks can help solve their business problems, provide technical leadership for customers to evaluate and adopt 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.
You will become an expert in, and promote Databricks inspired open-source projects (Apache Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars. Travel to customers in your region is also required.
Requirements:
- 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)
Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.