FEQ327R240

While candidates in the listed location(s) are encouraged to apply for this role, exceptionally well-qualified candidates in other East Coast locations will also be considered.

Mission

Solutions Architects at Databricks lead the growth of the Databricks Data Intelligence Platform. As a team, we have expertise in cloud platforms, data engineering, data analytics, and data science, machine learning, and AI. As a member of our team, you will exercise and grow your expertise in those areas, using open source projects such as Apache Spark™, Delta Lake, and MLflow. This is a customer-facing role, where you will work with customers, your teammates, the product team, our post-sales team,s and partners, to identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through the implementation, to accomplish meaningful outcomes for their businesses. In this process, you will build relationships with our customers, identify and cultivate champions, and establish yourself as a trusted advisor. You will report to a Field Engineering Manager within the Financial Services team at Databricks.

The impact you will have:

• 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, execute proof of concepts for strategic customer projects, and validate integrations with cloud services and other 3rd party applications
• Build and present reference architectures, how-tos, and demonstrate applications for customers
• Become an expert in, and promote open source projects (Apache Spark™, Delta Lake, MLflow, and Unity Catalog) across developer communities through meetups, conferences, and webinars
• Travel to meet with customers in your territory

What we look for:

• 8+ years in a customer-facing pre-sales role, or consulting role - preferably working with big-data technologies to solve data engineering and big-data analytical challenges
• Experience designing and architecting distributed data systems
• Comfortable programming in, and debugging, at least one of: Python, SQL, Scala, Java, or R
• Experience working with global system integrators, consulting organizations, or financial services technology, or financial services data providers is a positive differentiator
• Experience building solutions with public cloud providers such as AWS, Azure, or GCP
• Experience with Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
• Experience with Data Warehousing technologies (Ex: SQL, OLTP/OLAP/DSS)
• Undergraduate degree or higher in an engineering or mathematics discipline such as Computer Science, Applied Mathematics, Electrical Engineering, etc.)