Analytics Engineer

As an Analytics Engineer, you’ll be the mastermind behind creating trusted, reusable, and analytics-ready data products that drive smarter decisions across the consumer business unit. You’ll design key business metrics, build semantic models, and develop reliable datasets that form the backbone of self-service analytics, executive strategies, and cutting-edge AI capabilities.

Operating at the crossroads of business performance, data engineering, and governance, you’ll ensure that data isn’t just available - it’s clear, trustworthy, and scalable for everyone.

Without your expertise, teams would still be stuck with fragmented KPIs, manual reports, and inconsistent data - holding back growth, trust, and the future of AI-driven innovation.

Your Responsibilities:

• Design, build, and maintain trusted, business-focused data products, KPIs, and datasets; translate business ideas into reusable metrics; collaborate with Data Engineering to industrialize and support self-service analytics.
• Own KPI definitions and business rules, collaborate with Data Governance to ensure data quality and compliance, contribute to metadata and data lineage initiatives, and promote a single source of truth for CBU performance.
• Develop trusted, reusable data assets for self-service analytics, automate reports and processes, enhance the analytics stack and semantic layer, and improve scalability, performance, and maintainability of solutions.
• Prepare data for AI-driven analytics and natural language access, develop trusted datasets, evaluate new technologies to enhance user experience, and support the shift toward augmented analytics and self-service decision-making.
• Work closely with business stakeholders to understand their challenges, support analysts with reliable data assets, and promote standard metrics and automation to improve performance management.

• Experience & Education: At least a few years of experience in analytics engineering, BI development, or data product design; Bachelor’s or Master’s in engineering, data, statistics, or related fields.
• Business & Industry Knowledge: Strong understanding of telecom or commercial analytics, operational performance drivers, and ability to link analytics to business outcomes.
• Technical Skills: Proficiency in advanced SQL, data modeling, cloud platforms (preferably BigQuery), semantic modeling, and BI ecosystems; experience with data governance tools (e.g., DataGalaxy), transformation frameworks (e.g., dbt), and data quality management.

• Data Product & Asset Development: Proven ability to design reusable data products, industrialize analytical assets, and manage KPIs and business metrics effectively.

• Stakeholder & Communication Skills: Excellent stakeholder management and communication abilities. Fluent in English (knowledge of French is also desirable)

• Emerging Technologies & AI: Understanding of Generative AI use cases, LLM-based querying, conversational analytics, AI copilots, and ability to operate within human + AI workflows.
• Governance & Scalability: Strong knowledge of data governance principles, scalability, and ensuring data solutions meet governance and scalability standards.
• Fluent in English (knowledge of French is also desirable).

Pulled from the full job description

• Company car
• Food allowance, You will develop your full potential by working with highly skilled and passionate colleagues and through continuous training.

You will have the opportunity to shape the future of data at Orange Belgium and lead AI transformation projects in the country.

Moreover, you can count on a highly competitive and versatile compensation (market competitive salary, company car or legal mobility budget, homeworking and net allowance, performance bonus, meal vouchers) and benefits package.