Sr. Solutions Architect - Financial Services (wealth and Asset Management)

Databricks Databricks · Data AI · MA · Remote · Field Engineering - FE Direct Regulated

Solutions Architect for Databricks in Financial Services, focusing on Wealth and Asset Management. This role involves partnering with sales, providing technical leadership to customers, consulting on big data architecture, executing proof of concepts, and building reference architectures using the Databricks Data Intelligence Platform. The role emphasizes expertise in cloud platforms, data engineering, data analytics, and data science, machine learning, and AI, and promotes open-source projects like Apache 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

  • customer-facing pre-sales or consulting experience
  • big-data technologies
  • data engineering
  • data analytics
  • distributed data systems architecture
  • Python
  • SQL
  • Scala
  • Java
  • R
  • public cloud providers (AWS, Azure, GCP)
  • Data Engineering technologies (Spark, Hadoop, Kafka)
  • Data Warehousing technologies (SQL, OLTP/OLAP/DSS)

Nice to have

  • global system integrators
  • consulting organizations
  • financial services technology
  • financial services data providers

What the JD emphasized

  • 8+ 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_)