Solutions Architect Financial Services

FEQ326R322

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

Mission

Solutions Architects at Databricks lead the growth of the Databricks Unified Analytics Platform. As a team we have expertise in cloud platforms data engineering data analytics and data science machine learning and generative 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 teams 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 that process you will build relationships with our customers find and build champions and become 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 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 how-tos and demonstrate applications for customers
• Become an expert in and promote open-source projects (Apache Spark Delta Lake MLflow and Koalas) across developer communities through meetups conferences and webinars
• Travel to meet with customers in your territory

What we look for:

• 7 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 Financial Services customers 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.)