Solutions Architect (Fintech)

TL;DR

Solutions Architect (Fintech): Leading the growth of the Databricks Data Intelligence Platform for financial services clients with an accent on cloud architecture, data engineering, and AI integration. Focus on designing distributed data systems, executing proof of concepts, and establishing yourself as a trusted technical advisor for strategic customer projects.

Location: Must be based in Georgia, Illinois, Massachusetts, New York, or Washington, D.C. (Exceptionally well-qualified candidates in other East Coast locations will also be considered).

Salary: $180,000 – $247,500 USD

Company

Databricks is the data and AI company, creators of the Data Intelligence Platform, Apache Spark, Delta Lake, and MLflow.

What you will do

• Partner with sales teams to solve complex business problems using the Databricks platform.
• Provide technical leadership for customers evaluating and adopting data intelligence solutions.
• Consult on big data architecture and execute proof of concepts for strategic projects.
• Build and present reference architectures and demonstrate applications for customers.
• Promote open source projects like Apache Spark, Delta Lake, and MLflow within developer communities.
• Travel to meet with customers within your assigned territory.

Requirements

• 7+ years of experience in a customer-facing pre-sales or consulting role.
• Experience designing and architecting distributed data systems.
• Proficiency in at least one of: Python, SQL, Scala, Java, or R.
• Experience building solutions with public cloud providers (AWS, Azure, or GCP).
• Strong background in Data Engineering (Spark, Hadoop, Kafka) and Data Warehousing (SQL, OLTP/OLAP).
• Undergraduate degree in an engineering or mathematics discipline.

Nice to have

• Experience working with global system integrators or financial services technology providers.

Culture & Benefits

• Comprehensive benefits and perks tailored to your region.
• Opportunity to work with industry-leading open source technologies.
• Commitment to a diverse and inclusive workplace culture.
• Focus on professional growth and technical expertise in AI and data science.