About TP:

TP is the largest global customer service company offering outstanding career opportunities. Our team counts more than 500,000 colleagues in over 90 countries worldwide with more than 40 years of tradition. TP is listed on the Euronext Paris stock exchange, is part of the UN Global Compact initiative and is certified by Great Place to Work®.

Role Overview

The Business Intelligence Analyst is responsible for designing and maintaining end-to-end reporting and analytics solutions, transforming raw data into reliable, business-ready insights.

This role operates across the full BI pipeline - leveraging Python for data preparation and ingestion, SQL for core transformations and data modeling, and Excel Power Query, DAX, and Power BI for analytical modeling, KPI development, and reporting.

Working closely with business stakeholders, the analyst ensures data accuracy, translates requirements into scalable solutions, and delivers structured analytics that support both operational execution and strategic decision-making.

1. Key Responsibilities

Data Ingestion & Preparation

Use Python to clean, normalize, validate, and prepare raw data from multiple sources (files, databases).
Perform deduplication, enrichment, and structural transformations prior to loading.
Load and maintain processed datasets within the data warehouse.

Data Transformation & Modelling

Develop and maintain SQL-based transformations, views, and aggregations.
Apply business logic, classification rules, and KPI calculations at the data layer.
Optimize queries for performance, scalability, and reusability.
Maintain clear and consistent fact/dimension structures to support analytics.

Analytics Layer (Excel, Power Query & DAX)

Consume and refine datasets using Excel Power Query.
Build structured data models with defined relationships and granularity.
Develop advanced DAX measures for KPIs, SLA tracking, and time-based analysis.
Ensure accurate handling of business calendars, working hours, and edge cases.

Reporting & Visualization

Design and maintain Power BI dashboards for operational and management insights.
Develop Excel-based analytical reports where required.
Ensure KPI consistency across all reporting tools.
Support ad-hoc analysis and deep-dive investigations.

Quality, Governance & Collaboration

Validate data accuracy across the entire pipeline—from source to reporting layer.
Document transformations, calculations, and data logic.
Proactively identify data gaps, inconsistencies, and improvement opportunities.
Collaborate with stakeholders to align on requirements and outputs.

2. Technical Skills

Minimum Requirements:

Python – data preparation, transformation, and loading.
SQL (essential) – advanced querying, transformations, and optimization.
Excel Power Query – data shaping and preparation.
DAX – complex measures and time-based logic.
Strong understanding of data warehousing concepts (facts, dimensions, grain).

Preferred:

Power BI – data modeling, dashboards, and visualization.

Analytical & Professional Skills

Strong analytical thinking with high attention to detail.
Ability to work with complex, multi-source datasets.
Clear communication of insights to both technical and non-technical stakeholders
Ability to manage multiple priorities in a dynamic environment.

Preferred Qualifications

Experience in a centralized BI or data warehouse environment.
Exposure to large operational datasets (eg, contact center, sales, transactional data).
Experience with KPI frameworks, SLA metrics, and performance reporting.
Familiarity with data quality controls and validation processes.

What This Role Delivers

A scalable and reliable BI pipeline—from raw data to decision-ready insights.
Consistent and standardized KPIs across SQL, Excel, and Power BI.

Business Intelligence Analyst

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