Technical Support

The Role As a Technical Support Engineer, you are the first responder for our most important customers. You won’t just be answering "how-to" questions; you will be debugging complex data schemas, investigating API integrations, and translating customer business logic into technical configurations. You will live in Slack and Pylon, providing real-time, white-glove support that feels like an extension of the customer’s own team. Key Responsibilities Slack-First Support: Manage real-time customer interactions via dedicated Slack channels using Pylon. You will be responsible for triaging issues, maintaining fast response times, and ensuring no "ping" goes unanswered. Technical Troubleshooting: Deep-dive into the company platform to resolve issues related to: Data Connectivity: Troubleshooting Snowflake/BigQuery permissions and connection strings. Advanced Data Modeling: Helping customers refine their "Context Modeling" and domain-specific knowledge. API & Integrations: Assisting with GraphQL API implementation and Slack integration setups. Case Management: Use Pylon to track bugs, enhancement requests, and documentation gaps. You will own the lifecycle of a ticket from initial Slack message to engineering resolution. Live Consultations: Hop on video calls with customers to walk through complex "How-To" scenarios, such as creating custom metrics or configuring Row Level Access Control (RLAC). Voice of the Customer: Aggregate common friction points and missing features to provide structured feedback to our Product and Engineering teams. Documentation: Contribute to the firm Docs by turning common support resolutions into self-service guides. Technical Requirements Stack focus: SQL, APIs, AI/LLMs, Pylon Data & SQL: Strong ability to write and read SQL. You must be able to look at a query generated by Firm and understand why it might be returning a specific result based on the customer’s schema. The Wisdom Stack: Proficiency in (or ability to quickly learn) the technical pillars defined in our documentation: Building and managing Knowledge/Context Models. Setting up Evaluations Sets and Runs to test AI accuracy. Managing Workspaces, Organizations, and User Permissions. Working with Deep Analysis functionality and visualization properties. API Familiarity: Comfortable using tools like Postman or cURL to test GraphQL endpoints. Tooling: Experience with modern support stacks—specifically Pylon for Slack-based support—is a significant advantage. Qualifications The "Support Engineer" DNA: You are naturally curious and won't stop until you understand the root cause of a problem. Communication: You can explain a complex RAG (Retrieval-Augmented Generation) concept to a non-technical business user without losing them. Agility: You thrive in a fast-paced startup environment where the product evolves weekly. Empathy: You understand that when a data tool isn't working, it impacts a customer's ability to do their job. You handle high-pressure situations with a calm, helpful demeanor.

Required Skills ['Technical Support']

Additional Information

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