Keyrus

Customer Support

• Apoyar tareas administrativas y operativas del equipo, como control de aprobaciones, seguimiento de actividades y consolidación de información
• Documentar procesos internos y mantener actualizados los archivos del equipo
• Proponer e implementar automatizaciones simples (ej. en Excel, Teams o Forms) para mejorar la eficiencia operativa
• Apoyar la organización de reuniones, bitácoras de trabajo, y reportería básica
• Acompañar la ejecución de mejoras en flujos operativos junto a líderes del equipo

Aprendiz SENA – Customer Experience, CX

Data Engineer

• Collaborate with clients to understand business objectives and technical requirements, translating them into target-state data architectures and roadmaps that drive value.
• Own the architecture of end-to-end data initiatives: design and guide the build of scalable data pipelines, lakehouses, and architectures using Fabric, and other modern tools (Databricks, Snowflake, Azure Data Services, etc.).
• Model full end-to-end medallion lakehouse architectures (bronze, silver, gold), articulate them clearly to client stakeholders, and guide their implementation - ensuring scalability, data quality, governance, and performance.
• Design and own parameterized ingestion frameworks for batch and near real-time pipelines, including source connectivity across diverse systems (databases, APIs, files, streaming) and on-premises data gateways.
• Optimize pipeline and query performance -tuning Spark, partitioning, shortcuts, and incremental loads - to meet SLAs cost-effectively as data volumes scale.
• Design and optimize semantic models -star-schema modeling, DirectLake and Import tradeoffs, relationship and DAX optimization, and aggregations - so analytics layers stay performant and scale with the business.
• Design, implement, and operate CI/CD pipelines to enable reliable, automated deployments across environments.
• Define, promote, and enforce Fabric architecture standards and best practices across engagements.
• Provide technical leadership to cross-functional teams -data engineers, analysts, and business stakeholders - mentoring engineers and ensuring delivery aligns to the agreed architecture.
• Stay up to date with offerings and emerging technologies, recommending improvements and innovative solutions to meet business needs.

Data Architect

Business Intelligence Developer

• Design and deliver end-to-end Power BI solutions, covering data modelling, ETL integration, and dashboard development
• Engage directly with clients to gather requirements and define scalable BI architectures
• Translate business needs into technical designs and high-quality analytical solutions
• Define and promote Power BI best practices and architectural standards
• Collaborate with data engineers and analysts to ensure data readiness, quality, and alignment
• Implement secure and compliant Power BI data models and access controls
• Monitor and optimise solution performance for a seamless user experience
• Deliver training sessions, workshops, and enablement activities to increase adoption
• Provide advisory support, particularly for self-service BI enablement and governance frameworks
• Contribute to shaping BI strategy and long-term data vision with stakeholders

Senior Power BI Consultant

• Design, develop, and implement scalable, efficient data pipelines using Azure Databricks, Apache Airflow, and PySpark
• Ensure data quality, performance, and reliability
• Perform data analysis and troubleshooting
• Create interactive reports and dashboards in Power BI
• Actively collaborate on the design and implementation of new features and capabilities

Data Engineer, Azure

Data Scientist

• Identifier, cadrer et formaliser des cas d’usage Data Science
• Proposer et développer des POCs innovants
• Concevoir et entraîner des modèles de Machine Learning / Deep Learning
• Traiter et structurer des données complexes, parfois textuelles ou non structurées
• Collaborer avec les Data Engineers pour l’industrialisation des pipelines
• Participer aux activités R&D IA de Keyrus

Full-stack Engineer

• Define and evolve AI architecture choices: ML, deep learning, generative AI, LLMs
• Design robust, scalable AI solutions aligned with business objectives
• Ensure the technical quality of deliverables and oversee code reviews
• Drive technology choices and maintain active monitoring of AI innovations
• Establish engineering best practices (testing, code review, standards)
• Lead and develop a team of AI Engineers (junior to senior profiles)
• Structure AI engineering practices: code standards, MLOps, documentation
• Contribute to the recruitment and career development of AI profiles within Keyrus
• Run technical workshops and share knowledge within the practice
• Manage end-to-end production deployment of AI use cases (from POC to production)
• Design and implement advanced RAG architectures (ingestion, indexing, generation)
• Optimize GenAI systems (prompt engineering, fine-tuning, evaluation)
• Implement data pipelines and model monitoring systems
• Interact directly with clients: scoping, reporting, strategic advisory
• Ensure performance, security, and cost optimization of deployed AI solutions

Tech Lead AI

Product Manager

• Gérer et optimiser une plateforme data en collaboration avec des équipes pluridisciplinaires et multiculturelles
• Décliner la stratégie produit et assurer son amélioration continue
• Gérer la priorisation, le backlog et le suivi budgétaire
• Concevoir les fonctionnalités, les processus associés et rédiger les user stories
• Assurer la coordination et la communication avec les parties prenantes
• Promouvoir l’usage et la connaissance de la plateforme auprès des équipes projet et des stakeholders
• Recueillir et formaliser les besoins métier pour les intégrer à la stratégie produit
• Garantir la conformité des livrables avec les besoins initiaux (tests, qualité)
• Définir et suivre les KPI de la plateforme

Product Owner, Data

• Delivery / Conseil & Expertise: Conception et mise en œuvre d'architectures Data modernes (Cloud & On-premise)
• Réalisation d’audits, définition de roadmaps, accompagnement sur les choix technologiques
• Réalisation de PoC/MVP, coaching technique, conduite du changement
• Participation à l’écosystème tech (Meetups, afterworks, partenaires, éditeurs…)
• Contribution active à notre communauté d’experts Data (Snowflake, AWS, GCP, Azure, Databricks, DBT, Looker, Rivery, Airbyte, etc.)
• Accompagnement des équipes commerciales sur les réponses techniques
• Participation à la formalisation des offres et des convictions Data de l’agence
• Accompagnement de consultants en mission, animation de la communauté, recrutement, entretiens techniques

• Guidage des clients vers les solutions Data les plus pertinentes.
• Conception des écosystèmes robustes (Cloud, stockage, intégration).
• Transformation des données en insights stratégiques.
• Garantie de la qualité technique et fonctionnelle des solutions.
• Participation à la formation des équipes.

Tech Lead, Data

• Conceive, develop and industrialize reliable and high-performance data pipelines
• Integrate structured and unstructured data, both in batch and real-time
• Deploy and optimize data environments on the Cloud (AWS, Azure, GCP)
• Implement and orchestrate ETL/ELT processes (Talend, Airflow, dbt, Fivetran, etc.)
• Work on modern environments such as Databricks, Snowflake, BigQuery, Redshift
• Ensure data quality, security and governance
• Contribute to technology watch and recommend the best solutions for each project

Data Analyst

• Développement des flux ETL : Création et optimisation de pipelines de données robustes.
• Création de Dashboards interactifs et mise en place de KPIs : Rendre les données compréhensibles et exploitables.
• Support & Maintenance des reportings : Assurer une gestion efficace des flux.
• Gestion de Projet : Participer activement à la gestion de projet en toute autonomie.
• Méthode Agile : Travailler avec les équipes dans un environnement agile.
• Veille technologique & Certification : Rester à la pointe de la technologie et enrichir tes compétences.
• Accompagnement des juniors : Partage de ton expertise et développement des talents de demain.

• Design, implement, and maintain enterprise data warehouse solutions following Data Vault 2.0 methodology
• Develop and optimise Hubs, Links, Satellites, PIT, and Bridge tables
• Lead conceptual, logical, and physical data modelling activities across multiple initiatives
• Define and promote data architecture standards, modelling guidelines, naming conventions, and documentation practices
• Ensure scalability, performance, reliability, and maintainability of data warehouse architectures
• Provide technical leadership and architectural guidance to Data Engineers and development teams
• Drive the standardisation and automation of ELT processes, metadata management, and deployment practices
• Collaborate closely with Business Analysts, Product Owners, Data Governance teams, and other stakeholders to translate business requirements into robust data solutions
• Support reporting and analytics teams by delivering optimised and business-ready data structures

Aprendiz SENA – Customer Experience, CX

Data Architect

Senior Power BI Consultant

Data Engineer, Azure

Data Scientist

Tech Lead AI

Product Owner, Data

Data Architect

Tech Lead, Data

Data Engineer

Data Analyst

Senior Data Warehouse Architect, Data Vault 2.0