Solutions Architect - Financial Services
Lead pre-sales technical engagements for the Databricks Data Intelligence Platform within Financial Services. Design distributed data architectures, run POCs, and guide customers through implementation of Spark, Delta Lake, and MLflow solutions.
About the job
Responsibilities
- 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
Requirements
- 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 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.
Nice-to-Haves
- Experience working with global system integrators, consulting organizations, or financial services technology, or financial services data providers
Skills
Python, SQL, Scala, Java, R, AWS, Azure, GCP, Spark, Hadoop, Kafka, Delta Lake, MLflow, Unity Catalog
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