Data Architect

Data Architect

Hiring Model: CLT Safe
Work Model: Remote
Experience: +10 Years


Required Skills:

  • Proficiency in Analytics: Traditional BI, Data Ingestion, Data Preparation, Implementation, and Data Visualization.
  • Big Data knowledge, understanding of the Hadoop ecosystem, and Data Ingestion.
  • Big Data architecture (batch and fast).
  • Development of reference architectures (master data, analytics, operational).
  • Data Warehousing, Data Lake, and Business Intelligence.
  • Knowledge of Data Governance and Data Modeling.
  • Language: Technical English.

Technologies:

  • Apache Airflow / Apache Kafka / Apache Hadoop / Apache Spark.
  • Cassandra / MongoDB.
  • Cloud Providers (AWS, GCP, Azure).
  • Java/Maven, Python, Scala.

Experience:

  • Experience in Data Reference Architecture, a 360º view of Transactional, BI/Analytics architectures (responsibilities of each layer and respective solutions).
  • Proficiency in Analytics: Traditional BI, Data Ingestion, Data Preparation, Implementation, and Data Visualization.
  • Experience with structured databases (Oracle, SQLServer) and unstructured databases (MongoDB, Redis, Cassandra).
  • Structured and unstructured databases.
  • Big Data knowledge, understanding of the Hadoop ecosystem, and Data Ingestion.
  • Experience in big data architecture (batch and fast).
  • Experience with cloud computing solutions on platforms (AWS, Azure, Google Cloud Platform).
  • Experience in developing reference architectures (master data, analytics, operational).
  • Experience in solutions with data integration with Data Warehousing, Data Lake, and Business Intelligence.
  • Knowledge of data model repositories.
  • Knowledge of data governance.
  • Experience with DevOps tools.
  • Experience with data modeling.

Desirable Knowledge:

  • Knowledge of Enterprise Architecture (TOGAF standard).
  • Knowledge of Agile culture, Scrum framework.
  • Knowledge in Infrastructure, Network, Firewall, and Servers.
  • Experience in the process and architecture for the Data Protection Law (LGPD).
  • Development, maintenance, and optimization of ETL processes.
  • Completed degree in IT-related courses (Information Systems, Data Processing, Systems Analysis, Computer Science, Computer Engineering, Big Data, or related fields).

Day-to-Day Activities:

  • Identify storage and data processing requirements.
  • Build the model of areas of interest to the chain of conceptual models (business view).
  • Implement update mechanisms and document existing databases (data catalog).
  • Support development squads in the design and implementation of solutions, as well as support in the data modeling process.
  • Provide guidance on best practices and problem resolution.
  • Ensure accessibility, coherence, and security of data in technical solutions aligned with the company’s business areas.
  • Describe and maintain the information value chain (data lifecycle).

Key Activities/Deliveries:

  • Define and implement data modeling processes (relational, dimensional, and analytics, both conceptual, physical, and logical).
  • Map and provide views on existing data structures and their relationships, as well as future views and the roadmap for evolution.
  • Define data architecture, evaluate architectural proposals, and supervise implementations.
  • Document existing databases (data catalog).
  • Manage and disseminate Data Governance policies.
  • Manage Data Governance, optimization, and security practices of resources aligned with the company’s business.
  • Disseminate concepts related to LGPD.
  • Develop and document the data lifecycle in the company.
  • Define data modeling for NoSQL databases.

Soft Skills:

  • Sense of urgency in deliveries and challenging situations.
  • Proactivity (understand project business rules).
  • Resilience in difficult or crisis situations.
  • Flexibility in scenarios that require professionals to reinvent themselves.
  • Problem-solving ability through an analytical view and logical reasoning.
  • Proximity to development squads.
  • Holistic view of business and technological platforms.
  • Passion for quality.
  • Effective communication, empathy, collaboration, and interaction between teams with different aspects.

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