Sr. Solutions Architect - Gsi's and Fintech Data

Databricks Databricks · Data AI · San Francisco, CA · Field Engineering - FE Direct Regulated

Solutions Architect at Databricks focused on leading the growth of the Databricks Data Intelligence Platform within the Financial Services sector. This role involves partnering with sales, providing technical leadership, consulting on big data architecture, executing proofs of concept, and building reference architectures. The role emphasizes expertise in cloud platforms, data engineering, data analytics, and machine learning/AI, utilizing open-source projects like Spark, Delta Lake, and MLflow.

What you'd actually do

  1. Partner with the sales team to help customers understand how Databricks can help solve their business problems
  2. Provide technical leadership for customers to evaluate and adopt Databricks
  3. Consult on big data architecture, execute proof of concepts for strategic customer projects, and validate integrations with cloud services and other 3rd party applications
  4. Build and present reference architectures, how-tos, and demonstrate applications for customers
  5. 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

Skills

Required

  • 10+ years in a customer-facing pre-sales role, or consulting role
  • Experience designing and architecting distributed data systems
  • Comfortable programming in, and debugging, at least one of: Python, SQL, Scala, Java, or R
  • 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

Nice to have

  • Experience working with global system integrators, consulting organizations, or financial services technology, or financial services data providers
  • Experience building solutions with public cloud providers such as AWS, Azure, or GCP

What the JD emphasized

  • customer-facing pre-sales role
  • big-data technologies
  • data engineering
  • big-data analytical challenges
  • distributed data systems
  • Python
  • SQL
  • Scala
  • Java
  • R
  • global system integrators
  • consulting organizations
  • financial services technology
  • financial services data providers
  • public cloud providers
  • AWS
  • Azure
  • GCP
  • Data Engineering technologies
  • Spark
  • Hadoop
  • Kafka
  • Data Warehousing technologies
  • SQL
  • OLTP/OLAP/DSS
  • engineering or mathematics discipline
  • Computer Science
  • Applied Mathematics
  • Electrical Engineering