Senior Support Engineer - North America
Hive- Full Time
- Senior (5 to 8 years)
Candidates should possess a Bachelor's degree in Computer Science, Engineering, or a related field, and have at least 3 years of experience in a customer support role, with a preference for experience in a technical environment. Familiarity with distributed systems, Hadoop, cloud technologies, security, DBMSs, and navigating complex Java codebases is beneficial, as is experience with Docker and Kubernetes. Strong Linux skills and SQL exposure are also required, along with knowledge of authentication and authorization technologies, SSL/TLS, and languages such as SQL, Java, Python, and Bash.
As a Customer Support Engineer, you will be responsible for responding to and resolving Galaxy & SEP customer inquiries via chat, email, or call session, ensuring adherence to service level agreements. You will contribute to the customer-facing knowledge base, collaborate with pre and post-sales teams, and enthusiastically participate in ongoing personal learning through team training and development. Additionally, you will escalate and manage escalated issues with Engineering to ensure positive customer outcomes, demonstrating a desire to learn and work cross-functionally within a customer-success-oriented company.
Data analytics and SQL engine distribution
Starburst specializes in data analytics by providing a distribution and support for the Trino SQL engine, which is designed for efficient and scalable analytics on data lakes and various data sources. Their products, Starburst Galaxy and Starburst Enterprise, allow clients to access and analyze data quickly, whether in the cloud or on-premises. Starburst connects seamlessly with popular data visualization tools like Tableau, Power BI, and Looker, making it easier for users to integrate and access their data. What sets Starburst apart from competitors is its enhancement of the open-source Trino engine with additional connectors, security features, and dedicated enterprise support. The company's goal is to help organizations achieve faster data insights and better decision-making through improved analytics capabilities.