Sr. Manager, Data Analytics & CVM - BU

Purpose of the job

The Sr. Manager of Data Analytics & CVM Insights is responsible for defining and driving the analytics & insights strategy across Orange Egypts business units. The role focuses on transforming data into actionable insights, enabling CVM decisioning, and empowering B2C, B2B, Finance, Customer Experience, and Orange Cash with trusted analytics.

• He/she will lead the design of modern analytic data models, and build a strong insights layer on top of Oranges on-premise data lakehouse—powered by modern open-source technologies.
• This role requires a leader who can bridge business and technical teams, set the strategic direction for analytics, and ensure insights are consistent, scalable, and ready for AI enablement (EDA, feature exploration, segmentation fields)

Duties and responsibilities

1. Lead the design of Target Architecture and implementation of transformation program to achieve it, directing the evaluation of strategies and policies to ensure OEG vision & Business requirements are being met.

2. Design the competitive data architecture, including framework, principle, transformation roadmap and Lead the delivery team to realize an optimized solution.

3. Create robust, scalable, optimized and sustainable data architecture that supports Orange Egypts vision and the digital foot-print as well as business requirements and provides for future expansion

4. Identify Industry trends and areas of innovation in data tools and techniques, and recognize appropriate timing for adoption.

5. Work closely with Executive Management, internal Data factory peers and customer resources to ensure a smooth transition from the initial to the target unified Architecture.

6. Present and share Transformation program progress to relevant stakeholders including C-level thru regular steering committees

7. Interface with Orange group to align eco-system tools, and standardize built solutions

8. Re-engineer existing physical data structures and recommend efficiencies as it relates to data storage and retrieval

9. Design optimal data lake and analytics platform to fulfill the business/technical requirement. Enable Artificial and business intelligence tools and platforms to both BI Analysts and data scientists.

10. Identify the gap between business requirement and data architecture and propose solution to resolve or shorten the gap.

11. Build integrated Enterprise Data Warehouse and Data lake models using both Hadoop and relational models to support optimized reporting solutions

12. Work closely with DBAs , IT experts and data lake resources to help insure the physical design meets the functional and performance requirements of the applications utilizing the data

13.Collaborate with ETL, BI and API developers on data mapping and report/application design

Job specification

Education

BS/MS in Computer Science, Computer Engineering, Business Analytics, Statistics, or related fields.

Experience

10–15 years of experience in analytics, BI, or data strategy, with:

• Proven leadership in modern data analytics environments (not legacy-only DWH).
• Strong experience with:
• Data modeling & ELT/ETL
• Modern query engines (Trino, Presto, SparkSQL, etc.)
• Workflow orchestration (Airflow or similar)
• dbt or modular ELT frameworks
• A plus is a Deep experience generating insights for CVM or customer-centric analytics (telecom experience preferred, but not mandatory).

• Experience in decisioning environments (campaign management, segmentation, personalization).
• Experience in telco, fintech, e-commerce, or large-scale consumer industries.
• Exposure to modern BI platforms (Tableau, Metabase, PowerBI, Looker).

• Exposure to big-data thinking and scalable architectures (Kafka, distributed SQL engines).
• Understanding of AI analytics requirements (EDA, feature exploration, data readiness).
• Experience with cross-functional stakeholder management.

Skills and Abilities

• Strong leadership with the ability to coach and grow analytics teams.

• Deep business acumen, particularly in customer value, churn, segmentation, and monetization.

• Strong communication skills with ability to present insights to senior leadership.

• Strategic thinker with the ability to connect data to business impact.

• Advanced SQL skills and solid understanding of data modeling principles.

• Analytical mindset with proven experience turning data into action