• Definir la estrategia analítica y el modelo funcional de la solución, traduciendo objetivos de negocio en decisiones de arquitectura. • Diseñar y construir el pipeline de ingesta y transformación sobre AWS: funciones Lambda (integradas con Microsoft Graph API), Data Lake en S3, jobs de Glue y tablas externas en Athena. • Configurar la seguridad de la infraestructura (IAM) y, según corresponda, su capa de red, asegurando que la arquitectura cumpla los estándares exigidos en entornos regulados como el financiero. • Diseñar el modelo dimensional (star schema) pensado para escalar a nuevas entidades sin rediseño, y el modelo de seguridad a nivel de datos (RLS), incluyendo su mapeo a la identidad corporativa del cliente. • Definir los estándares de arquitectura, métricas de negocio y consultas analíticas que el equipo de desarrollo ejecuta. • Actuar como autoridad técnica frente al cliente: validar la calidad de los entregables del equipo y ser el punto de contacto para decisiones de arquitectura e infraestructura. • Mantener la documentación de arquitectura como base de gobierno y transferencia de conocimiento.

Role Description This is the contact point for the local team to work closely with the headquarter teams. We are seeking an experienced Senior Data Engineer to design, implement, and maintain our data infrastructure and pipelines. The ideal candidate will have a strong background in data engineering, big data technologies, and cloud platforms. You will work closely with data scientists, analysts, and other stakeholders to ensure efficient and reliable data processing and storage solutions and who has mind set things to done. - Design, develop, and maintain scalable data pipelines and ETL processes - Implement and optimize data storage solutions, including data warehouses and data lakes - Collaborate with data scientists and analysts to understand data requirements and provide efficient data access - Ensure data quality, consistency, and reliability across all data systems - Develop and maintain data models and schemas - Implement data security and access control measures - Optimize query performance and data retrieval processes - Evaluate and integrate new data technologies and tools - Mentor junior data engineers and provide technical leadership - Collaborate with cross-functional teams to support data-driven decision-making Qualifications - Bachelor's or master's degree in computer science, Engineering, or a related field - 7+ years of experience in data engineering or related roles - Strong programming skills in Python, Java, or Scala - Extensive experience with big data technologies such as Hadoop, Spark, and Hive - Proficiency in SQL and experience with both relational and NoSQL databases - Experience with cloud platforms (AWS, Azure,) and their data services - Knowledge of data modeling, data warehousing, and ETL best practices - Strong problem-solving skills and attention to detail - Excellent communication and collaboration skills Requirements - Experience with stream processing technologies (e.g., Kafka, Flink or delta live table) - Familiarity with data governance and compliance requirements - Experience with containerization and orchestration tools (e.g., Docker, Kubernetes) - Contributions to open-source projects or relevant certifications - Experience in Tencent big data platform - Experience in PowerBI will be preferable Benefits - 16~20 days of fully-paid annual leaves - Full social insurance and housing fund - Year-end bonus - WLB - No business trip - Best Culture - Clear focus - Diverse Workplace (Our members are from around the world!) - Non-hierarchical and agile environment - Growth opportunity and career path

Role Description This is the contact point for the local team to work closely with the headquarter teams. We are seeking an experienced Senior Data Engineer to design, implement, and maintain our data infrastructure and pipelines. The ideal candidate will have a strong background in data engineering, big data technologies, and cloud platforms. You will work closely with data scientists, analysts, and other stakeholders to ensure efficient and reliable data processing and storage solutions and who has mind set things to done. - Design, develop, and maintain scalable data pipelines and ETL processes - Implement and optimize data storage solutions, including data warehouses and data lakes - Collaborate with data scientists and analysts to understand data requirements and provide efficient data access - Ensure data quality, consistency, and reliability across all data systems - Develop and maintain data models and schemas - Implement data security and access control measures - Optimize query performance and data retrieval processes - Evaluate and integrate new data technologies and tools - Mentor junior data engineers and provide technical leadership - Collaborate with cross-functional teams to support data-driven decision-making Qualifications - Bachelor's or master's degree in computer science, Engineering, or a related field - 7+ years of experience in data engineering or related roles - Strong programming skills in Python, Java, or Scala - Extensive experience with big data technologies such as Hadoop, Spark, and Hive - Proficiency in SQL and experience with both relational and NoSQL databases - Experience with cloud platforms (AWS, Azure,) and their data services - Knowledge of data modeling, data warehousing, and ETL best practices - Strong problem-solving skills and attention to detail - Excellent communication and collaboration skills Requirements - Experience with stream processing technologies (e.g., Kafka, Flink, or delta live table) - Familiarity with data governance and compliance requirements - Experience with containerization and orchestration tools (e.g., Docker, Kubernetes) - Contributions to open-source projects or relevant certifications - Experience in Tencent big data platform - Experience in PowerBI will be preferable Benefits - 16~20 days of fully-paid annual leaves - Full social insurance and housing fund - Year-end bonus - WLB - No business trip - Best Culture - Clear focus - Diverse Workplace (Our members are from around the world!) - Non-hierarchical and agile environment - Growth opportunity and career path

• Lead the design, maintenance, and evolution of conceptual and logical information models that enable shared understanding of core business concepts across the organisation. • Own and contribute to central information architecture artefacts such as the Enterprise Data Model and Data Domain Map, ensuring alignment across domains and initiatives. • Lead definition and adoption of business concepts, taxonomies, and semantic standards. • Collaborate closely with business stakeholders, data product teams, solution architects, and engineers to translate business needs into clear information models that guide downstream implementations. • Ensure alignment between information architecture, data governance policies, and quality expectations. • Assess as‑is and define target‑state information flows supporting interoperability and lineage. • Set guardrails and best practices for information modelling across initiatives. • Guide teams in applying enterprise information models in local delivery contexts. • Promote reuse‑first and business‑aligned modelling principles. • Educate, guide, and coach stakeholders and architects, helping to embed information architecture thinking across teams. • Mentor architects and contribute to capability building across the architecture community. • Contribute to continuous improvement of architecture tooling and ways of working, including integration with data catalogues and metadata management tools.