You must be a senior Cloud Native Data Architect, combining a strong technical background in modern data
architecture with expertise in implementing data architectures, collaboration skills, and innovative
mindset to contribute effectively.

Proven experience as a Data Architect with a focus on designing and implementing scalable data architectures
• Extensive experience with databases, data lakes, and data warehouses and message brokers (e.g.: Kafka)
• Extensive experience with ETL processes and data integration from various sources
• Extensive experience with modern data technologies and cloud services.
• Proficient in designing and implementing data models to meet business requirements.
• Knowledge of and experience with Data Mesh
• Ability to evaluate and recommend the adoption of new tools and technologies.
Innovative mindset to propose solutions enhancing the organization’s data architecture
Must-have experience
• A minimum experience of 3 years as a Cloud Native Data Architect
• Deep understanding of data architectures (incl. data quality and data SLOs) in the context of cloud-native and
distributed environments and the ability to articulate data concepts to different audiences
• Proven experience in helping development teams navigate the CAP theorem with trade-offs when choosing data
storage technologies
• Experience in building data solutions that enable data democracy in the organization and prevents data silos while
ensuring data governance and compliance
• Strong knowledge of data security and the ability to specify at an architectural level the security best practices that
must be incorporated when working with Data (encryption, access control, data classification and compliance, etc)
• Demonstrated experience in explaining the maturity required to use cloud native data technologies – not only on the
IT side but especially on the Business side of an enterprise.
• Prior experience with the following technologies:
o Relational Databases (eg: PostgreSQL)
o NoSQL Databases (eg: MongoDB, Cassandra)
o Time series Databases (eg: TimescaleDB, InfluxDB)
o Graph Databases (eg: Neo4j)
o Data Warehouse and Data Lake architectures
o Messaging/Data Streaming Systems (Apache Kafka)
o Data processing and workflows (eg: Spark, Dagster, Apache Airflow, etc)
• Proficiency in at least one programming language – Python, Java or Scala
• Familiarity with agile development methodologies and tools (e.g., Scrum, SAFE, JIRA, Confluence).