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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Analytics Engineer - **Company:** Orange - **Location:** Evere, Belgium (Remote available) - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Business Intelligence Development, BigQuery, Cloud Computing, Information Engineering, Data Governance, Data Systems, Digital Assets, Sql Optimization, Large Language Models, Generative AI, Data Lineage, Collibra, Automation Anywhere - **Published:** July 17, 2026 - **Apply:** https://be.indeed.com/viewjob?jk=fb6bf70e34ad96c3 ## About the Role * 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). ## Description 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. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Making Data Warehouses fast. 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