Job Description: * Bachelor’s degree in Computer Engineering, Computer Science, Information Systems, Data Science, or related fields; * Master’s degree or postgraduate qualification in related fields is desirable; * Solid experience in corporate data engineering and architecture, with hands-on involvement in end-to-end pipeline development and maintenance; * Experience working in hybrid environments (on-premises and cloud) and in digital transformation or data migration projects; * Experience in data modeling, integration, and governance; * Prior experience with enterprise BI tools (e.g., QlikSense, Power BI, or similar); * Technical English proficiency for reading documentation and data frameworks is desirable. * Ensure reliability, scalability, and efficiency of the corporate data ecosystem, providing the necessary technical foundation to support business strategic decision-making, enterprise BI, and Flora’s Artificial Intelligence (AI) initiatives. * Design, implement, and maintain an end-to-end data platform, internalizing critical capabilities and driving technological evolution and data environment governance. * Design and evolve the corporate data architecture, ensuring scalability and performance; * Manage development, staging, and production environments, including automated provisioning; * Administer storage and processing layers (Redshift, SQL Server, Jenkins, Hope, and future integration with Snowflake); * Implement security and compliance practices, including encryption, data segregation, and access policies aligned with LGPD; * Monitor environment costs and performance, proposing continuous improvements; * Develop and maintain ingestion pipelines from ERPs, APIs, legacy systems, and structured/unstructured files; * Standardize connectors, templates, and frameworks for reuse and versioning; * Ensure data quality at the source through schema, volume, and integrity validations; * Create and maintain data models across Bronze, Silver, and Gold layers, ensuring traceability and consistency; * Apply data transformation frameworks (DBT, Spark, SQL, Python) and data engineering best practices; * Automate data quality tests and pipeline validations; * Orchestrate data workflows (via Jenkins, Airflow, or similar tools), ensuring reliable execution and adherence to defined SLAs; * Implement monitoring routines, alerts, and incident management; * Document critical processes, workflows, and integrations; * Support QlikSense environment governance, ensuring certified models and datasets; * Contribute to the corporate data catalog and glossary (BigQuery and GCA); * Collaborate with the Data Governance team on LGPD policy implementation and sensitivity classification; * Develop and manage secure APIs for data delivery to business areas; * Support the creation of data-driven applications and automations, integrating systems and enhancing operational efficiency 2512080202191852863