Data & AI Platform / Solution Architect Master - Lisboa - 04/11/25

Local ( distrito, região): Lisboa

Função:Data & AI Platform / Solution Architect Master

Nível: SR

Data de início: Imediato

Duração da contratação: 1 ano

Inglês B2

Português e Espanhol - Opcional

Must Have

• Degree in Software Engineering or Computer Engineering or similar
• Knowledge of the Energy and Utilities market and GDPR;
• Up-to-date knowledge of databases and analytical technologies, including data lake/lakehouse architectures and No
  SQL storage.
• Experience with Cloud Platforms (one or more: AWS, Google, Azure)
• Knowledge of data governance and data security practices
• Knowledge of Machine Learning, algorithms, and statistical models (such as classification, time series analysis, regression, etc. )
• Experience in metadata management, data catalogs, data standards, and master data management best practices
• Experience with Big
  Data databases (one or more: Big
  Query, Azure Synapse, AWS Red
  Shift, Cassandra, Couchbase, HDFS);
• Certification – CELONIS;
• Proven experience in technology implementations – CELONIS;
• Solution Architect specialized in DATA, ANALYTICS and AI to design software applications (NOT DEVELOP)
• Technical expertise of Data, Analytics and AI development.

Nice to Have

• Experience in strategic projects
• Knowledge of Agile methodology, JIRA, and Confluence
• Experience in the Utilities, mainly retail, sector
• Experience with either SAP and/or Sales
  Force applications

Top Skills

• Understanding of the Energy and Utilities market
• Familiarity with GDPR compliance
• Data modeling (normalized, denormalized, star schema, graph, time series, document)
• Experience with data streams, API integrations, and data frameworks
• Design of scalable, secure, and
  - performance data architectures
• Experience with AWS, Google Cloud, or Azure
• Proficiency in Big
  Data databases (Big
  Query, Azure Synapse, Red
  Shift, Cassandra, Couchbase, HDFS)
• Knowledge of data lake/lakehouse architectures and No
  SQL storage
• Expertise in data governance, data security, metadata management, and master data management
• Familiarity with data catalogs, data lineage, and data standards
• Knowledge of ML algorithms and statistical models (classification, regression, time series)
• Experience defining Data
  Ops observability indicators
• Ability to optimize for performance, scalability, and reliability
• CELONIS certification and proven implementation experience
• Technical-functional analysis and platform improvement
• Solution design documentation in Confluence