Sr. Solutions Architect - AI Natives Business (AI)

Location: Remote; Pacific Time preferred, Mountain Time considered. Travel to customers in the assigned region is required.

Salary: $219,100–$301,300 USD.

Company

Databricks is a Data and AI company providing a unified platform for data engineering, analytics, machine learning, and AI applications.

What you will do

• Partner with sales teams and provide technical leadership to help customers solve business problems with the Databricks platform.
• Consult on big data architectures and implement proofs of concept across data engineering, data science, machine learning, and SQL analysis workflows.
• Validate integrations with public cloud services, internal tools, and third-party applications.
• Collaborate with customers, product teams, Solutions Architects, and the broader customer-facing organization.
• Guide customers through competitive landscapes, best practices, implementation, and technical champion development.
• Promote Databricks-inspired open-source projects including Spark, Delta Lake, and MLflow.

Requirements

• 7+ years of experience in data engineering, data science, technical architecture, or a similar pre-sales or consulting role.
• Experience building distributed data systems.
• Proficiency in programming with and debugging Python and SQL.
• Experience building solutions with public cloud providers such as AWS, Azure, or GCP.
• Expertise in either data engineering technologies such as Spark, Hadoop, or Kafka, or data science and machine learning technologies such as pandas, scikit-learn, PyTorch, or TensorFlow.
• Availability to travel to customers in the assigned region.

Nice to have

• Degree in a quantitative discipline such as Computer Science, Applied Mathematics, or Operations Research.
• Databricks Certification.

Culture & Benefits

• Remote work with Pacific Time preferred and Mountain Time considered.
• Compensation may include an annual performance bonus, equity, and regional benefits.
• Inclusive hiring practices and a diverse workplace.
• Actual compensation is based on skills, experience, certifications, training, and work location.