Databricks is seeking a Solutions Architect for Financial Services (Banking and Payments) to lead customer engagements and design architectures using the Databricks Unified Analytics Platform. This is a customer-facing, on-site role based in the United States. You will partner with the sales team to articulate the value of Databricks, provide technical leadership for evaluating and adopting the platform, and architect distributed data systems. You will validate integrations with cloud services and third-party applications, build reference architectures, write how-tos, and develop demo applications. You will promote Databricks’ open-source projects (Spark, Delta Lake, MLflow, Koalas) to developer communities through meetups, conferences, and webinars. Travel to customers in your region is required. What we look for: 7+ years in a customer-facing pre-sales, technical architecture, or consulting role; experience designing distributed data systems; programming in Python, Scala, Java, SQL, or R; experience with AWS/Azure/GCP; data engineering technologies (Spark, Hadoop, Kafka); data warehousing (SQL, OLTP/OLAP); experience with financial services clients is a plus. Desired degree in a quantitative discipline.

Databricks is seeking a Solutions Architect for Financial Services (Banking and Payments) to lead customer engagements and design architectures using the Databricks Unified Analytics Platform. This is a customer-facing, on-site role based in the United States. You will partner with the sales team to articulate the value of Databricks, provide technical leadership for evaluating and adopting the platform, and architect distributed data systems. You will validate integrations with cloud services and third-party applications, build reference architectures, write how-tos, and develop demo applications. You will promote Databricks’ open-source projects (Spark, Delta Lake, MLflow, Koalas) to developer communities through meetups, conferences, and webinars. Travel to customers in your region is required. What we look for: 7+ years in a customer-facing pre-sales, technical architecture, or consulting role; experience designing distributed data systems; programming in Python, Scala, Java, SQL, or R; experience with AWS/Azure/GCP; data engineering technologies (Spark, Hadoop, Kafka); data warehousing (SQL, OLTP/OLAP); experience with financial services clients is a plus. Desired degree in a quantitative discipline.