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As a Senior Customer Experience (CX) Data Analyst at Tabby, you will drive data-informed improvements to customer support operations through analytics, reporting, and process optimization. You'll partner closely with CX, product, operations, and QA teams to measure agent and support performance, identify operational bottlenecks, and enable better decision-making across support workflows.
Key responsibilities include analyzing large-scale datasets on agent performance, support interactions, and quality assurance metrics. You'll write optimized SQL queries in BigQuery and ClickHouse, build dashboards in Tableau or Metabase, and detect behavioral and performance trends. You'll use LLM tools and prompt engineering for daily analytical tasks, summarization, and insights generation, including assessing LLM output quality and integrating model outputs into analytical workflows.
You'll also own automation and workflow optimization, working with Airflow and Python to automate data tasks, optimize analytics pipelines and data marts, and refactor inefficient DAGs and queries for scalability and cost-effectiveness. You'll translate business inefficiencies into trackable metrics and suggest improvements to agent tooling, ticket routing, and SLA tracking.
This role requires 3+ years of data analytics experience in fast-paced, data-heavy environments. You'll need advanced SQL proficiency (BigQuery/ClickHouse), strong Python skills for data analysis and automation, experience with data visualization tools (Tableau, Metabase, Looker), and understanding of Airflow and modern data pipelines. Experience with LLM agents, prompt engineering, and API usage is essential. You should excel at translating business questions into testable hypotheses and communicating findings to both technical and non-technical stakeholders. Upper-intermediate or higher English proficiency is required.
