DOMVS iT

• Juntar-se a um ambiente colaborativo e inovador. • Ajudar na implementação e melhoria do SAP AFS para nossos clientes no setor de moda. • Atuar na identificação e diagnóstico de problemas. • Contribuir em projetos de migração e evolução em SAP.

• Atuar como referência técnica e funcional do ERP TOTVS Protheus, apoiando as áreas de negócio na utilização dos módulos e funcionalidades da solução. • Identificar oportunidades de melhoria por meio dos recursos nativos do sistema. • Prestar suporte funcional aos usuários. • Levantar e documentar requisitos para customizações quando necessário. • Atuar como interface entre as áreas de negócio e as consultorias responsáveis pelo desenvolvimento e evolução do ERP.

• Work on the implementation and evolution of the SAP FI module – General Ledger (GL). • Gather requirements from business areas and prepare functional specifications. • Configure accounting processes in SAP S/4HANA. • Support the construction of the accounting equivalence engine for automatic posting generation. • Define and validate accounting rules and financial integrations. • Validate integration processes using the Journal Entry API (OData/SOAP). • Support Cash Management projects, bank reconciliation, and integration with financial institutions. • Specify developments for the ABAP team using BAPIs, BAdIs and standard SAP APIs. • Participate in unit, integrated, UAT and Go-Live testing. • Support the development of analytical models using CDS Views and Fiori applications. • Ensure adherence to SAP S/4HANA best practices and Clean Core.

• Develop, maintain and optimize data pipelines using Python. • Design, build and maintain ETL/ELT processes. • Develop integration solutions between different data sources. • Model and structure data for Data Lake and Data Warehouse. • Work on ingestion, transformation and provisioning of data in an AWS environment. • Monitor and optimize performance of data pipelines and data processes. • Implement data engineering best practices, version control and code quality standards. • Collaborate with Analytics, BI, Data Science and Development teams. • Participate in defining the architecture of cloud data solutions. • Support incident resolution and continuous improvement of the data platforms.

• Capacity Monitoring: Monitor Fabric Capacity Metrics / FUAM daily to prevent and mitigate throttling and performance degradation in the environment. • Performance Tuning: Investigate slow or heavy reports and semantic models, performing reverse engineering to optimize DAX and data structures. • Governance and Administration: Manage the data lifecycle (DevOps/Git/Deployment Pipelines), audit access and security (RLS/OLS), and organize workspace topology. • Consultative Role (Evangelization): Engage with report developers from other departments (Shadow IT) to diagnose root causes of slowness, advise on best practices, and negotiate refresh windows. • Architecture Evolution: Support architectural decisions on when to use Lakehouse, Warehouse, or semantic models in Direct Lake, integrating with the existing data ecosystem.

• Maintain and evolve corporate data environments • Develop, maintain and optimize ETL (Extract, Transform, Load) processes • Perform database maintenance and tuning to ensure performance, availability and data integrity • Administer and support SAS environments, including tasks related to SAS DBA and SAS DI Studio (SIS) • Support legacy applications and processes, proposing continuous improvements • Monitor, analyze and address failures in data load and integration processes • Handle a significant volume of tickets, meeting established SLAs and ensuring operational continuity • Assist in identifying and resolving incidents related to the data environment • Produce and maintain technical documentation for processes and procedures • Participate in continuous improvement, automation and data architecture modernization initiatives • Support projects related to the implementation and evolution of the Data Lake

• Develop and maintain backend systems; • Collaborate with front-end teams for integration; • Participate in the design and implementation of software architecture; • Ensure code quality through testing and code reviews.

• Evolve the ETL pipeline focusing on performance (filtering, joins, deduplication, aggregation). • Optimize reading/writing of large files (CSV, Parquet, gzip). • Design and operate persistence in PostgreSQL (schema, indexes, queries). • Implement caching, server-side pagination and sorting for large datasets. • Ensure stability and scalability of processing.

• Develop, train, and validate supervised and unsupervised Machine Learning models; • Perform statistical and mathematical analyses to identify patterns, trends, and opportunities; • Work with exploration, preprocessing, and modeling of large volumes of data; • Build analytical pipelines and data preparation processes; • Create predictive studies, segmentations, and recommendation models; • Support business areas in data-driven decision making; • Develop dashboards and executive presentations with analytical insights; • Monitor performance and accuracy of deployed models; • Collaborate with Data Engineering, BI, and business teams; • Ensure best practices for documentation, governance, and model versioning.

• Develop, implement and maintain ETL (Extract, Transform and Load) processes to integrate data from multiple sources. • Develop, optimize and maintain Stored Procedures, Views, Functions and Queries in SQL Server, ensuring high performance and scalability. • Ensure data quality, integrity and consistency by identifying, analyzing and correcting issues in integration processes. • Design and organize databases to facilitate information consumption by analysts, managers and other company areas. • Provide operational support for the Cash Reconciliation tool, performing configurations, adjustments, validations and technical support for users. • Understand and apply business rules related to financial reconciliation, working together with Treasury, Accounting and Operations teams. • Participate in requirements gathering with stakeholders, proposing improvements to processes, integrations and data flows. • Develop solutions that promote greater accessibility, governance and democratization of information to support decision-making. • Monitor and optimize data loading and integration processes to ensure stability, reliability and operational efficiency.