• Scaling the Warehouse: Partner with our Analytics Engineer to refactor and optimize our dbt pipelines, ensuring they remain fast and cost-efficient as our data volume grows. • Internalizing Ingestion: Bridge the gap between product data and BI by maintaining and extending ingestion scripts (Go/Python) to ensure we have the data we need, when we need it. • Data Intelligence: Build the pipelines that power internal "intelligence" features, such as automated customer segmentation, sentiment classification, and qualitative research tools. • Operational Excellence: Strengthen our data activation layer, ensuring our CRM and operational tools stay in sync with the warehouse. • Governance & Trust: Drive initiatives around data lineage, documentation, and quality testing to maintain high trust in our reporting. • Advanced dbt Modeling: Build modular, well-tested SQL models using dbt. You’ll focus on the "heavy lifting" of the transformation layer—macros, incremental strategies, and performance tuning. • Pipeline Engineering: Maintain and optimize custom ingestion workflows and orchestration, ensuring high availability and reliability. • Intelligence & Automation: Implement internal automation workflows that leverage LLMs for data classification and insights generation within the warehouse. • Data Activation: Own the "Reverse ETL" flows that push critical business signals back into GTM tools for Sales, Marketing, and Success. • Technical Standards: Contribute to our engineering culture through code reviews, documentation, and the enforcement of data contracts with upstream providers.

Role Description We are looking for an Analytics Engineer to help scale the "engine" behind our business intelligence — at a moment when that engine is expanding its mandate. - Partner with data and engineering teams, as well as backend engineers, Sales/RevOps, Marketing, and Product and AI Engineering stakeholders. - Build reliable, high-performance pipelines while contributing to ingestion, orchestration, and LLM-powered classification workflows. The Impact You’ll Have - Scaling the Warehouse: Partner with our Analytics Engineer to refactor and optimize our dbt pipelines. - Internalizing Ingestion: Maintain and extend ingestion scripts (Go/Python) to ensure data availability. - Data Intelligence: Build pipelines for internal "intelligence" features like automated customer segmentation and sentiment classification. - Operational Excellence: Strengthen our data activation layer to keep CRM and operational tools in sync with the warehouse. - Governance & Trust: Drive initiatives around data lineage, documentation, and quality testing. What you’ll do - Advanced dbt Modeling: Build modular, well-tested SQL models using dbt. - Pipeline Engineering: Maintain and optimize custom ingestion workflows and orchestration. - Intelligence & Automation: Implement internal automation workflows leveraging LLMs for data classification. - Data Activation: Own the "Reverse ETL" flows for critical business signals. - Technical Standards: Contribute to engineering culture through code reviews and documentation. Qualifications - The dbt Specialist: Significant experience building and managing complex dbt projects. - Data Warehouse Expert: Deep experience with Google BigQuery or similar cloud warehouses. - Polyglot Developer: Proficient in SQL and Python, with interest in Go. - The Governance Advocate: Disciplined about documentation and establishing clear lineage. - Ops-Minded: Care about data freshness and reliability; experience with Airflow and Docker is a plus. - Automation Enthusiast: Excited about using modern tools for data classification and insights. - Collaborative Team Player: Strong communicator who enjoys partnering with cross-functional stakeholders. Operating Principles - Engineering standards: Git workflows, pull‑request reviews, code owners, automated tests. - Lineage & documentation: Keep dbt docs current and track exposures. - Incremental delivery: Ship improvements iteratively with fallbacks and backfill plans. - Partnership: Co‑design models with stakeholders and make trade‑offs explicit. Benefits - Private life and health insurance plan. - Fully remote work if preferred, apart from team meetings a few times per year. - Your personal annual training budget. - An annual home office allowance to set up your personal space. - Company laptop. - 23 days of paid time off. - 3 early summer Fridays in July and August. - Access to AI tools at work. - A free LearnWorlds School to build and sell your own courses. - Work in one of the globally top 5 e-learning courses platforms. - An opportunity to grow alongside us and shape the future of e-learning. - An entrepreneurial, international, and highly motivated team with a flat hierarchy. - Annual company retreats.

Role Description Responsable de optimizar los procesos de monitoreo y análisis de datos en la plataforma relacionadas con la subgerencia de CX. - Automatización de procesos gestión de calidad y CX: - Identificar oportunidades de automatización en los procesos relacionados con la subgerencia de CX (ACEC, DominIA, Aula, entre otras). - Diseñar e implementar soluciones de automatización utilizando RPA y otras herramientas. - Mantener y optimizar los procesos automatizados. - Análisis de datos: - Recolectar, limpiar y transformar datos de diversas fuentes. - Realizar análisis exploratorio y estadístico de los datos. - Crear reportes personalizados y visualizaciones de datos para comunicar los hallazgos. - Recomendaciones estratégicas: - Diseñar, actualizar y desarrollar maquetas para visualizar los resultados de los análisis. - Crear prototipos de nuevas funcionalidades para los distintos modelos de la subgerencia. - Soporte técnico CX: - Brindar soporte técnico y asistencia a los usuarios internos en el uso de las herramientas y aplicaciones. - Resolver incidencias y problemas relacionados con la plataforma asignadas. - Mejora continua: - Proponer mejoras en los procesos existentes y nuevas funcionalidades para la plataforma de la subgerencia (nuevas o existentes). - Mantenerse actualizado en las últimas tendencias. Qualifications - Profesional en Sistemas, Administración de Empresas, mercado, técnico. - Dominio de herramientas de gestión de bases de datos y generación de reportes. - Mínimo 3 años de experiencia en roles similares. - Experiencia en el uso de herramientas de análisis de datos (Excel avanzado). - Conocimiento en la ejecución de aplicativos como speech. - Conocimiento en gestión de calidad, CX, mejora continua. Selection Process El proceso de selección se realiza a través de Aira - plataforma de reclutamiento diseñado para mejorar tu experiencia de postulación. Para postular solo necesitas: - Postular a la oferta. - Revisar tu email. - Ingresar a Aira y contestar las preguntas y/o pruebas solicitadas. Luego, si vemos que tu perfil se ajusta a lo que estamos buscando, te contactaremos por email (a través de Aira) para seguir a la etapa presencial. Company Description Somos Entel Connect. Nuestro propósito es ayudar a transformar la experiencia de los usuarios, integrando tecnologías, procesos y personas cercanas, aportando al desarrollo de tu negocio y la sociedad. Buscamos personas que sientan como su cliente, que inspire y movilice, liderando los cambios con excelencia en sus resultados.

Role Description Unser Bereich Customer Management entwickelt und betreibt auf einer skalierenden AWS-Infrastruktur eine wachsende Zahl an datengetriebenen Lösungen mit signifikantem Business Impact. Dafür arbeiten Platform Engineers, Data Engineers und Data Scientists gemeinsam an modernen Technologien, um unseren Fachabteilungen maßgeschneiderte, datengetriebene Services zur Verfügung zu stellen. - Produktentwicklung und Betrieb: Du stellst den reibungslosen operativen Betrieb eines AWS-basierten Produkts zur Ermittlung von Kundenpräferenzen sicher und entwickelst dieses stetig weiter. - End-to-End Projektarbeit: Von der Konzeption bis hin zur Analyse begleitest Du Projekte gemeinsam im Team. - Data Engineering: Die Entwicklung unserer Daten-Pipelines liegt in Deiner Hand. - Datenqualität und Betrieb: Du etablierst Datenqualitätsprüfungen, Monitoring und Alerting und unterstützt beim Incident-Handling. - Produkt und Business-Logik: Du implementierst Business-Logik im Produkt und stellst sicher, dass Anforderungen sauber in Datenstrukturen und Transformationen übersetzt werden. - Stakeholdermanagement: Du stehst im engen Austausch mit den Fachbereichen zur Abstimmung von Betrieb und Plattform-Ausrichtung. Qualifications - Abgeschlossenes Studium (z. B. Physik, Mathematik, Informatik, Wirtschaftswissenschaften) oder eine vergleichbare Qualifikation. - Mindestens 3 Jahre Berufserfahrung als Analytics Engineer, Data Scientist, Data Engineer oder in einer vergleichbaren Rolle. - Sehr gute Python-Kenntnisse für die Pipeline- und Softwareentwicklung. - Gute SQL-Kenntnisse für die Datenmodellierung und -analyse. - Erfahrung im Aufbau, Betrieb und in der Wartung von Daten-Pipelines. - Routinierter Umgang mit modernen Software-Engineering-Praktiken (Git, Code Reviews, CI/CD, Testing). - Praktische Erfahrung mit AWS (z. B. Glue, Lambda, Step Functions); Kenntnisse in Spark/Databricks sind ein Plus. Benefits - Mobiles Arbeiten. - Flexible Arbeitszeiten. - Gesundheitsvorsorge. - Mitarbeitervergünstigungen. - Team- und Firmenevents. - Mitarbeiterfahrzeug. Contact Dennis Rahim HR-Manager