Senior Data Analyst
Skills
About This Role
Overview
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.
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