Resident Solution Architect

Responsibilities

• Collaborate with customers to understand their business goals, data architecture, and technical requirements.
• Design end-to-end solutions that leverage Starburst products to address customer needs, including data access, analytics, and performance optimization.
• Develop architectural diagrams, technical specifications, and implementation plans for customer projects.
• Lead the implementation and deployment of Starburst solutions, working closely with customer teams and internal stakeholders.
• Learn in depth how the engine, connectors and integrations with 3rd party products work.
• Provide technical guidance and best practices to customers on using Starburst products effectively.
• Work with partners to train and upskill external personnel on Starburst Products for successful delivery.
• Collaborate with internal teams and external partners to create resources, best practices, application flow diagrams and internal processes that enhance partner delivery capabilities.
• Troubleshoot and resolve technical issues that arise during the implementation and operation of Starburst solutions.
• Stay current on industry trends, emerging technologies, and best practices in data management and analytics.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field. Master's degree preferred.
• 8+ years of experience in a technical role, such as solution architect, data engineer, or software engineer.
• Deep understanding of data architecture principles, including data modeling, data integration, and data warehousing.
• Proficiency in SQL and experience with distributed query engines (e.g., Presto, Trino, Apache Spark).
• Strong problem-solving skills and the ability to think strategically about business challenges and technical solutions.
• Excellent communication and interpersonal skills, with the ability to effectively interact with customers and internal teams.

Nice-to-Haves

• Experience with Linux OS, cloud platforms (AWS, Azure, Google Cloud), containerization technologies (Docker, Kubernetes) and programming/scripting (Java, Python, Bash).
• Prior experience in client facing / consulting roles.
• Prior experience with open-source technologies and contributions to the open-source community.
• Prior experience with running technical training internally or externally.
• Familiarity with LLM-based data interaction patterns (e.g., natural language to SQL, retrieval-augmented generation).
• Understanding of AI governance, data security, and risks associated with AI-generated queries and insights.

Compensation

Pay Range: $115,000—$150,000 USD (inclusive of variable compensation such as commission or bonus). All employees receive equity packages (ISOs) and comprehensive benefits.