Senior AI Solutions Architect - Data & ML Platform (Remote)

Neon; San Francisco (CA); Remote; USD 219,000 - 301,000; Full time

Job summary

Databricks is seeking a Sr. Solutions Architect on the AI native team supporting the Digital Natives business.

You will shape the future of the big data landscape by collaborating with world-class data engineering and data science teams, guiding customers through architecture and implementation using our platform and APIs. You will partner with sales, provide technical leadership, develop technical champions, and promote open-source projects like Spark, Delta Lake, and MLflow.

Qualifications

• 7+ years in data engineering, data science, or pre-sales/consulting.
• Experience building distributed data systems.
• Proficiency in Python and SQL.
• Experience with AWS/Azure/GCP.
• Spark, Hadoop, Kafka; Pandas, Scikit-learn, PyTorch, TensorFlow.
• Willingness to travel to customers.
• Databricks Certification is a plus.

Responsibilities

• Lead technical discussions with customers and sales to design architecture and solutions.
• Develop proofs-of-concept and validate integrations with cloud services and third-party tools.
• Collaborate with Solutions Architects and customer teams to deliver end-to-end data and analytics architectures.
• Promote and recruit contributors for Databricks-inspired open-source projects like Spark, Delta Lake, and MLflow.

Skills

Distributed data systems

Python

SQL

Cloud platforms

Spark/Hadoop/Kafka

Pandas/Scikit-learn/PyTorch/TensorFlow

Willing to travel

Senior pre-sales/consulting

Databricks Certification

Education

Bachelor's degree in a quantitative discipline

Job description

Databricks is seeking a Sr. Solutions Architect on the AI native team supporting the Digital Natives business.

You will shape the future of the big data landscape by collaborating with world-class data engineering and data science teams, guiding customers through architecture and implementation using our platform and APIs. You will partner with sales, provide technical leadership, develop technical champions, and promote open-source projects like Spark, Delta Lake, and MLflow.