Senior Data Analyst

Tabby

1d

About The Position

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.

Requirements

• 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.

Responsibilities

• 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.
• 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.

Benefits

• Inclusive company culture, embracing diversity, integrity and transparency.
• Strive for work-life balance.
• Caring and nurturing for employees.
• 100% trust and freedom to apply own vision and come up with ideas.
• Encourage everyone to think and make decisions like Tabby was their own business.
• Employee stock options programme available for everyone.
• Opportunity to learn and grow in one of the fastest growing fin tech companies in the region.
• Relocation support and guidance through the process.
• Devices required for work will be provided.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed