Keyrus

AI Engineer

• Co-create solutions with business and technology stakeholders through workshops, rapid iterations, and hands-on delivery
• Translate use cases into production-ready GenAI and agentic AI solutions, including RAG architectures, intelligent assistants, and AI-enabled workflows
• Prototype, test, deploy, monitor, and improve solutions in real customer environments

Forward Deployed AI Engineer

Cloud Engineer

• Responsible for designing, developing and evolving data integration and processing solutions.
• Ensure quality, scalability and performance in modern analytical environments.

Senior Data Engineer – AWS

Business Intelligence Developer

• Continuously monitor the capacity of the Microsoft Fabric environment, tracking consumption and performance metrics to prevent bottlenecks, degradations, and throttling.
• Investigate performance issues in reports, semantic models, and analytical processes, performing troubleshooting and identifying root cause.
• Perform optimizations on data models, queries, and DAX expressions to ensure greater efficiency and an improved user experience.
• Manage platform administration and governance, including: organizing Workspaces; access and security management (RLS/OLS); version control with Git; deployment pipelines; and artifact lifecycle governance.
• Work consultatively with business stakeholders and development teams, promoting best practices for Power BI and Microsoft Fabric.
• Support architectural decisions involving Lakehouse, Data Warehouse, Direct Lake, and semantic models.
• Proactively monitor logs, metrics, and platform usage to anticipate incidents before they impact production.
• Support legacy analytical solutions in on-premises environments, ensuring stability and operational continuity of existing integrations and models using SSIS and SSAS.

Senior BI & Data Governance Analyst – Microsoft Fabric

Data Engineer

• Design, develop, and maintain scalable data pipelines using Databricks, PySpark, Python and SQL.
• Build and optimise batch and near real-time data processing solutions on the Microsoft Azure ecosystem.
• Develop and maintain Delta Lake-based data architectures.
• Develop robust and scalable data products and modern data platform components supporting strategic business initiatives.
• Contribute to CI/CD implementation and automation for data solutions.
• Apply engineering best practices around source control, testing, deployment, and monitoring.
• Support Infrastructure-as-Code and environment standardisation initiatives.
• Ensure high standards of data quality, observability, monitoring, security, and operational reliability.
• Collaborate with Product Managers, Architects, Data Engineers, and business stakeholders to deliver high-quality outcomes.
• Participate in technical design discussions and contribute to solution architecture decisions.
• Support platform governance, cost optimisation, technical documentation, and knowledge sharing initiatives.

Senior Data Engineer, Databricks

Salesforce Consultant

• Definir y priorizar el roadmap de producto digital (eCommerce, app, servicio al cliente) en función de impacto de negocio.
• Gestionar el backlog y trabajar con equipos multidisciplinarios (UX, desarrollo, QA, marketing) bajo metodologías agile/scrum.
• Liderar iniciativas de SEO y optimización de UX/UI orientadas a conversión (CRO).
• Coordinar la estrategia digital de Customer Service integrada a la plataforma (chat, CRM, devoluciones/garantías).
• Gestionar el producto de la app móvil (nativa o PWA): release management funcional, adopción, ASO.
• Supervisar el funnel de eCommerce end-to-end: catálogo, checkout, pagos, promociones e inventario visible al cliente.
• Definir requerimientos de negocio para procesos de integración entre plataformas (ERP, CRM, OMS, PIM, pasarelas de pago) y validar que resuelven el problema funcional.
• Gestionar la relación con proveedores y agencias externas de implementación.
• Traducir métricas de negocio en roadmap, y roadmap técnico en lenguaje de negocio.

Senior Product Owner – Salesforce Commerce Cloud Consultant

Full-stack Engineer

• Como Fullstack Developer (Magento), serás responsable de asegurar la evolución, estabilidad y mantenibilidad de aplicaciones web enfocadas en entornos e-commerce
• Desarrollar y mantener aplicaciones web basadas en PHP
• Participar en desarrollos fullstack, abordando tanto componentes de backend como de frontend
• Implementar nuevas funcionalidades en plataformas Magento
• Ejecutar mantenimiento evolutivo y correctivo
• Corregir errores y optimizar componentes existentes
• Colaborar con el equipo técnico en la definición de soluciones viables y sostenibles
• Gestionar y versionar cambios mediante Git
• Trabajar con bases de datos relacionales
• Aplicar buenas prácticas de desarrollo como clean code y documentación técnica
• Participar en pruebas y validación de desarrollos

Fullstack Developer, Magento

Ecommerce

• Liderar la arquitectura de soluciones eCommerce basadas en Magento / Adobe Commerce
• Definir y liderar la arquitectura funcional y técnica de soluciones eCommerce
• Diseñar plataformas escalables, seguras y de alta disponibilidad
• Traducir requerimientos de negocio en soluciones técnicas viables y sostenibles
• Diseñar integraciones con sistemas corporativos (ERP, CRM, OMS, PIM, pagos, logística, marketing automation, analítica)
• Establecer estándares técnicos, patrones de diseño y buenas prácticas de desarrollo
• Participar en la planificación de releases, estimaciones y roadmap tecnológico
• Realizar revisiones de arquitectura, código y diseño de soluciones
• Identificar riesgos técnicos y definir planes de mitigación
• Asegurar la correcta implementación trabajando con equipos de desarrollo, QA y DevOps
• Liderar iniciativas de optimización de performance, seguridad y experiencia de usuario
• Acompañar la resolución de incidentes críticos en producción
• Brindar liderazgo técnico y mentoría a equipos

Solution Architect, Magento Ecommerce

QA Engineer

• Asegurarás la calidad funcional, integración y experiencia de usuario en una plataforma de eCommerce basada en Magento (Adobe Commerce)
• Diseñar y ejecutar casos de prueba funcionales, de integración, regresión y smoke testing
• Validar módulos clave como catálogo, búsqueda, carrito, checkout, pagos, promociones y órdenes
• Realizar pruebas de APIs y validar integraciones con ERP, CRM, pasarelas de pago y sistemas de logística
• Identificar, documentar y gestionar defectos en herramientas como Jira
• Participar en ceremonias ágiles (Planning, Daily, Refinement, Retrospectives)
• Validar requerimientos y asegurar el cumplimiento de criterios de aceptación
• Ejecutar pruebas de regresión previas a despliegues
• Analizar resultados, realizar retests y verificar correcciones
• Validar experiencia de usuario en entornos cross-browser y responsive
• Contribuir a la optimización continua de procesos de calidad

QA Engineer, Magento Ecommerce

Technical Project Manager

• Lead and oversee projects related to Master Data Management (MDM) initiatives.
• Facilitate agile ceremonies, including Daily, Planning, Review, and Retrospective.
• Ensure proper application of agile practices and principles.
• Act as a liaison between technical teams, business areas, and stakeholders.
• Support the team in removing impediments and resolving conflicts.
• Promote continuous improvement of processes, practices, and workflows.
• Monitor performance indicators and agile metrics such as Velocity, Lead Time, Throughput, and Burndown.
• Support technical discussions related to Master Data Management platforms and processes.
• Ensure visibility of risks, dependencies, and project timelines.
• Conduct executive alignments and status reporting for leadership.

Senior Technical Project Manager, MDM

Solutions 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 & Solution Architect – Fabric

• Develop and scale enterprise web applications using Angular
• Integrate frontend applications with Python/FastAPI backends
• Implement GPT/LLM-based modules to support evaluation, automation, and workflow optimisation
• Design, build, and consume REST APIs within a microservices architecture
• Implement secure authentication and authorisation mechanisms
• Collaborate closely with Data Science and platform teams to integrate AI capabilities
• Participate in technical architecture discussions and contribute to system design decisions
• Ensure scalability, maintainability, and performance of applications
• Contribute to Agile ceremonies and delivery planning
• Support deployment, integration, and release activities across environments

Senior AI Engineer – German Speaker

Customer Success Manager

• Support the preparation and execution of CRM marketing campaigns.
• Perform audience counts and targeting analyses to support campaign planning.
• Configure campaign workflows and communication channels within CRM platforms.
• Coordinate campaign assets, approvals, and proofing activities.
• Monitor campaign execution and ensure quality standards are maintained.
• Collaborate with marketing and operational teams throughout the campaign lifecycle.
• Contribute to delivering engaging customer communications across multiple channels

CRM Campaign Assistant

• Lead the execution and coordination of CRM marketing campaigns.
• Act as the primary liaison between marketing stakeholders and campaign operations teams.
• Monitor campaign performance and delivery KPIs.
• Produce campaign reports and performance insights.
• Identify opportunities for process improvements and operational efficiency.
• Support and mentor junior CRM Campaign Assistants.
• Ensure campaign quality, consistency, and compliance with established processes.

CRM Campaign Specialist

Data Analyst

• Gather and analyse business requirements from stakeholders.
• Translate business needs into data workflows and reporting solutions.
• Develop Dataiku workflows and reconciliation processes.
• Create impactful Power BI dashboards and visualizations.
• Monitor data quality and perform validation activities.
• Generate actionable insights to support decision-making.
• Support compliance, controls, and operational reporting initiatives.

Data Analyst – Dataiku

• Design, develop, and maintain Dataiku workflows and data pipelines.
• Build data ingestion, transformation, and reconciliation processes.
• Develop SQL and Python solutions supporting business requirements.
• Implement data quality controls and monitoring mechanisms.
• Translate business needs into scalable technical solutions.
• Support data governance and lineage initiatives.
• Contribute to workflow automation and process industrialization.