• Define and work within our data governance practices, including a catalog/dictionary and management of data quality, so that users understand and can trust what they are reporting about • Manage lights-out data operations of our ETL/ELT pipelines ranging from streaming inputs to batch file loads, to support customer reporting, development, and operations • Untangle, normalize, synthesize as needed to permit joining and comparisons from disparate sources, and further analysis including ML processing • Wrangle internal and external data into and through the reporting pipeline and schema • Design and run the security aspects of reporting – we manage healthcare and payments data; a safety mindset is at the foundation of everything we do • Handle reporting requests from stakeholders within and external to the business; over time, move from adhoc to systematic • Support data analysts and other internal consumers of the data • Support and enable ML/AI workloads

Role Description Plongez au cœur de l’innovation dans le domaine de l’énergie en rejoignant une équipe dynamique et experte ! Notre client, un acteur de référence dans la gestion des installations hydroélectriques, recherche un.e data engineer dans le cadre de son programme Cyber et principalement sur son projet de collecte et valorisation de logs à destination de la cybersurveillance. Dans le cadre de votre mission, vous serez amené à effectuer diverses tâches : - Intégration de briques logicielles : Kafka, Opensearch/Elastic Search, Airflow, Rsyslog - Développement (Python / Bash) - Architecture technique cyber NOC/SOC/VOC - Architecture et Urbanisation Qualifications - Admin Linux - Notions de réseau (QoS, Bande passante, Protocoles…) - Challenge technique de l'architecture étudiée en phase de POCs (rendu : note d'analyse) - Architecture fonctionnelle et technique déployée sur les matériels en intégration puis en production - Contribution au document d’architecture technique - Respect du process DevSecOps en termes de développement logiciel interne Company Description Orange Business est un intégrateur réseau et numérique qui comprend toute la chaîne de valeur du monde digital, permettant à nos clients de se concentrer sur les initiatives stratégiques qui font avancer leur business. Chaque jour, vous collaborerez avec une équipe dédiée à la livraison de solutions globales cohérentes et durables, peu importe où nos clients opèrent. - Avec plus de 30 000 salariés en Europe, Asie, Amérique et Afrique - Nous proposons un environnement dynamique et innovant permettant de développer et affiner vos compétences - Nous offrons des opportunités passionnantes dans la data et le digital, le cloud, l'IA, la cybersécurité, ou encore l'IoT et le digital workspace

• Participating in the design and development of Data solutions for challenging projects. • Develop projects from scratch with minimal supervision and strong team collaboration. • Be a key player in fostering best practices, clean, and reusable code. • Develop ETLs using Spark (Python/Scala). • Work on cloud-based projects (Azure/AWS). • Build scalable pipelines using a variety of technologies.

Role Description We are looking for a strong Analytics Engineer to take charge of data transformation and build a reliable foundation for our marketing analytics. You will work at the intersection of Data Engineering and Data Analytics, turning the "chaos" of API exports into structured data marts. What You Will Do - Design and Development: Build and maintain scalable data models in Snowflake and BigQuery using dbt. - Data Modeling: Translate marketing business logic (LTV, CAC, attribution, cohort analysis) into clean, optimized SQL code. - Pipeline Optimization: Ensure Data Quality and freshness; set up tests and documentation within dbt. - Tech Stack: Work with a modern Modern Data Stack. We use the best tools available for transformation and storage. - Collaboration: Work closely with Growth Hackers and Marketers to understand their data needs. Qualifications - SQL Mastery: You write complex, readable, and efficient queries. You know your window functions and understand the specific dialects of Snowflake/BigQuery. - dbt (Data Build Tool): Experience with dbt (Core or Cloud) is mandatory. You know what ref, macro, and incremental models are and why tests are necessary. - Cloud Data Warehousing: Deep understanding of Snowflake or Google BigQuery architecture. - Marketing Domain: Understanding metrics (ROAS, ROMI, Retention) and how ad platforms (FB, Google Ads) operate is a massive plus. - Engineering Mindset: Proficiency with Git, an understanding of CI/CD, and adherence to DRY (Don't Repeat Yourself) principles. Benefits - Reshape marketing with us. Let’s work! By submitting your application, you agree to our Privacy Policy.