Senior Solutions Architect — Data & AI Platform

Menlo Ventures; California (MO); Hybrid; USD 219,100 - 301,300; Full time

Job summary

Databricks is seeking a Solutions Architect with deep customer-facing pre-sales experience to lead architectures for our Unified Analytics Platform. You will partner with Sales, craft reference architectures, and guide customers through implementations, leveraging Spark, Delta Lake, MLflow, and Koalas in cloud environments.

The role emphasizes technical leadership, open-source advocacy, and regional travel to engage with customers and partners, reporting to Field Engineering.

Qualifications

• 8+ years in a customer-facing pre-sales, technical architecture, or consulting role.
• Experience designing and architecting distributed data systems.
• Proficient in Python, Scala, Java, SQL, or R.
• Experience with public cloud providers (AWS/Azure/GCP).
• Background with Spark, Hadoop, Kafka, and data warehousing concepts.
• US Citizen.

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, implement proofs of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications.
• Build and present references architectures, how-tos, and demo applications for customers.
• Become an expert in, and promote Databricks inspired open-source projects across developer communities through meetups, conferences, and webinars.
• Travel to customers in your region.

Skills

Python

Scala

Java

SQL

R

Distributed systems

Education

Quantitative degree (CS/Applied Math/OR)

Tools

Spark

Hadoop

Kafka

Job description

Databricks is seeking a Solutions Architect with deep customer-facing pre-sales experience to lead architectures for our Unified Analytics Platform. You will partner with Sales, craft reference architectures, and guide customers through implementations, leveraging Spark, Delta Lake, MLflow, and Koalas in cloud environments.

The role emphasizes technical leadership, open-source advocacy, and regional travel to engage with customers and partners, reporting to Field Engineering.