Data Architect

Description

**Position Objective** ----------------------- Serve as a Data Architect, responsible for defining, evolving, and maintaining the organization's data architecture to ensure data quality, scalability, and alignment with business needs. The professional will play a strong consultative role with business units and provide technical leadership for strategic data and analytics projects. **Key Responsibilities** -------------------------------- * Act as the liaison between business and technology teams, translating business requirements into efficient and scalable data solutions. * Define and evolve the enterprise data architecture (structured and analytical). * Lead end-to-end data projects, ensuring delivery with quality, on schedule, and under proper governance. * Establish data standards, best practices, and frameworks (modeling, ingestion, transformation, and consumption). * Promote transparency and clarity in communication with both technical and non-technical stakeholders. * Demonstrate ownership of implemented solutions, ensuring their sustainability and evolution. * Collaborate closely with engineering, analytics, and business teams to enable integrated solutions. * Support strategic decision-making through reliable and well-structured data. **Behavioral Competencies (Soft Skills)** ---------------------------------------------- * Excellent communication with business units, capable of translating technical concepts into accessible language. * Transparency and clarity in communication, especially in project contexts and critical decision-making. * Strong sense of ownership, with accountability for deliverables and outcomes. * Ability to provide technical leadership and lead multidisciplinary projects. * Proactivity and strategic vision for evolving the data ecosystem. * Ability to influence stakeholders and promote sound data practices. **Desired Technical Requirements** --------------------------------- * Solid experience with relational databases: Oracle SQL; SQL Server. * Experience with cloud-based data platforms, especially: Microsoft Azure (Data Factory, Synapse, Data Lake, etc.). * Experience with distributed data processing: Databricks (Spark is considered a plus). * Proficiency in programming languages: Python for developing data pipelines and data automation. * Experience with DevOps practices applied to data: CI/CD and data pipelines; Code versioning (Git); Automated deployment. * Experience in data modeling (conceptual, logical, and physical). * Knowledge of modern data architecture (Data Lake, Lakehouse, etc.). **Languages** ----------- * Advanced English (reading, writing, and communication in meetings with global teams). **Differentiators** ---------------- * Experience with data governance and Data Quality. * Familiarity with Data Catalog and Data Lineage tools. * Experience with Oracle or SAP environments integrated into the data ecosystem. Experience in architecture modernization projects (on\-premises* cloud). ### **Department:** Corporate