Senior Data Analyst (CX)

As a Customer Experience (CX) Data Analyst, you will play a key role in improving how we support our customers through data driven insights and operational analytics. You will work closely with CX, product, and operations teams to measure performance, identify improvement opportunities, and support better decision making across support workflows. This role focuses on analytics, reporting, and process optimization, with exposure to automation and AI powered tools as part of everyday analytical work. Data Analysis & Insights - Analyze large-scale datasets related to agent performance, support interactions and QA. - Write optimized SQL queries using tools like BigQuery and ClickHouse. - Build dashboards in Tableau, Metabase. - Detect behavioral and performance trends among agents and support teams. - Partner with QA to identify root causes in agent behavior and customer issues. LLM & Prompting - Use LLM tools with practical prompt engineering for daily analytical tasks, summarization, and insights generation. - Ability to assess and profile LLM outputs for quality, relevance, and analytical correctness in business contexts. - Familiarity with LLM APIs and integrating model outputs into analytical or internal tooling workflows. Automation & Workflow Optimization - Work with Airflow and Python to automate data tasks and support workflows. - Optimize analytics pipelines and data marts to improve performance, resource efficiency, and reliability. - Identify and refactor inefficient DAGs, queries, and transformations to ensure scalable and cost-effective data processing. - Suggest and co-build improvements in agent tooling, ticket routing, and SLA tracking. - Translate business inefficiencies into trackable metrics and measurable outcomes. Cross-Functional Collaboration - Act as an analytical partner to Operations, Support Management, QA, and Training. - Work with Data Engineering to ensure clean, accurate, and well-modeled data pipelines. - Communicate findings clearly through presentations, visualizations, and concise documentation. - 4+ years of experience as a data analyst in a fast-paced, data-heavy environment. - Advanced SQL skills (preferably in BigQuery and/or ClickHouse). - Proficiency in Python for data analysis, automation, and integration tasks. - Experience with data visualization tools (e.g. Tableau, Metabase, Looker). - Understanding of Airflow, DAG orchestration, and modern data pipelines. - Experience with LLM agents, prompt engineering, and API usage. - Experience with forecasting and / or machine learning would be an advantage. - Ability to translate business questions into structured, testable hypotheses. - Strong presentation and storytelling skills; able to communicate with technical and non-technical stakeholders alike. - Upper-Intermediate or higher English proficiency (spoken and written). - We are an international Team of inspired professionals located all over the globe. - We have an inclusive company culture, embracing diversity, integrity and transparency. We strive for work-life balance and cherish the moments you spend with your loved ones, off-work. In the same spirit as for our product, we are caring and nurturing for our employees. - Our people are granted 100% trust and freedom to apply their own vision and come up with their ideas from day 1 at Tabby. You are the one who takes responsibility for your area of work. We encourage everyone to think and make decisions like Tabby was their own business, well because it is. Our employee stock options programme is available for everyone. - You will have an opportunity to learn and grow in one of the fastest growing fin tech companies in the region - We offer you relocation support as well as we guide you through all the process. - We’ll set you up with the devices required for your work.

3+ years of experience as a data analyst in a fast-paced, data-heavy environment. Advanced SQL skills (preferably in BigQuery and/or ClickHouse). Proficiency in Python for data analysis, automation, and integration tasks. Experience with data visualization tools (e.g. Tableau, Metabase, Looker). Understanding of Airflow, DAG orchestration, and modern data pipelines. Experience with LLM agents, prompt engineering, and API usage. Ability to translate business questions into structured, testable hypotheses. Strong presentation and storytelling skills; able to communicate with technical and non-technical stakeholders alike. Upper-Intermediate or higher English proficiency (spoken and written).

Analyze large-scale datasets related to agent performance, support interactions and QA. Write optimized SQL queries using tools like BigQuery and ClickHouse. Build dashboards in Tableau, Metabase. Detect behavioral and performance trends among agents and support teams. Partner with QA to identify root causes in agent behavior and customer issues. Use LLM tools with practical prompt engineering for daily analytical tasks, summarization, and insights generation. Ability to assess and profile LLM outputs for quality, relevance, and analytical correctness in business contexts. Familiarity with LLM APIs and integrating model outputs into analytical or internal tooling workflows. Work with Airflow and Python to automate data tasks and support workflows. Optimize analytics pipelines and data marts to improve performance, resource efficiency, and reliability. Identify and refactor inefficient DAGs, queries, and transformations to ensure scalable and cost-effective data processing. Suggest and co-build improvements in agent tooling, ticket routing, and SLA tracking. Translate business inefficiencies into trackable metrics and measurable outcomes. Act as an analytical partner to Operations, Support Management, QA, and Training. Work with Data Engineering to ensure clean, accurate, and well-modeled data pipelines. Communicate findings clearly through presentations, visualizations, and concise documentation.