• Capture and translate customer processes • Structure data and build the analytics foundation • Turn data into product insight • Be a technical face of the company externally

• Operationalize data collection instruments for research and evaluation-related surveys into scalable, accurate, consistent, and user-friendly tools via our Qualtrics platform. • Implement and maintain user access to support data privacy and minimum required access to protect data integrity in collaboration with technology and product teams. • Identify and implement solutions to translate hard copy surveys into Qualtrics software while preserving intended meaning, logic, and Institutional Review Board requirements. • Build and maintain flexible Qualtrics libraries that support consistency in data collection across survey instruments while building processes that manage version control. • Undertake robust quality assurance processes to ensure that surveys are accurately and consistently deployed to partners. • Proactively manage and resolve bugs within the Qualtrics system, including responding to inquiries from partners across JED to address any identified issues. • Collaborate with colleagues on the communications and product teams to ensure that all Qualtrics survey tools are accessible and ADA-compliant for all users. • Develop and maintain documentation related to Qualtrics research and evaluation data infrastructure, including but not limited to library infrastructure, key decision-points, bugs that might affect data quality, and user access procedures. • Conduct routine data management procedures to monitor the quality of JED’s data while identifying real-time and ongoing opportunities to improve data quality. • Utilize Qualtrics and JED’s data warehouse infrastructure to develop routine reports for critical data elements and develop feedback loops with partners to improve data quality. • Lead the day-to-day development and execution of data management best practices (e.g., data user and management documentation, survey version crosswalks and codebooks). • Collaborate with Research and Evaluation team members to ensure identified coding practices are operationalized within the data, with routine quality checks. • Conduct regular data quality audits and recommend quality improvement processes. • Generate and execute regular data cleaning procedures in collaboration with the Senior Analytics Specialist. • Identify opportunities across data sets to streamline data collection, including by reducing redundancies across systems, in collaboration with partners across JED. • Ensure compliance with all relevant data protection regulations and ethical standards. • Develop and enforce policies to maintain the confidentiality and integrity of sensitive information. • Stay updated on best practices in data collection and management.

• Responsible for project management of all the data management services for the assigned projects • Ensures the contracted Non CRF Data Management activities for projects are carried out by the Company in accordance with the executed contract and the Sponsor’s expectations • Acts as Functional Lead for Data Management including primary contact for internal liaison between Data Management/Operations and Project Management, Clinical Monitoring, and other functional groups • Coordinate the work of the assigned Data Management/Data Operations team • Communicate independently, proactively and clearly to internal and external stakeholders, able to work autonomously on the non-CRF data strategy for the study team • Take ownership of non-CRF data • Provide comprehensive assessment to identify all non CRF data types defined in the study protocol via protocol review and team discussion (including amendments) • Support implementation of patient enrollment and randomization strategy responsible for set up of IXRS UAT • Implement, maintain and approve non CRF Vendor Transfer Agreements/plans/ specifications • Confirm non CRF vendor specifications can be met and provide expertise on testing/results • Effectively communicates non-CRF data collection deliverables, status of work and data issues to the Client study lead and other study team members • Coordinates cross-functional non-CRF tasks with strong understanding of downstream processes and stakeholder needs and impacts • Receive, process, and deliver non CRF test and production data • Ensures launch, delivery and completion of all Data Management activities and milestones according to contractual agreement and relevant Standard Operating Procedures (SOPs), guidelines, and regulations • Provides project specific training to internal and external audiences as required • Responsible for financial management of assigned projects / programs, including revenue recognition, changes in scope and participation in internal project review meetings, including liaison with Finance and Contracts groups as needed • Monitors and communicates project progress to the Sponsor and project team including use of project status reports and tracking tools/metrics to enable in stream data collection and query management • Plan, manages and requests resources for assigned projects • Develop and maintain project plans, specifications and documentation in line with SOP requirements • Maintains documentation on an ongoing basis and ensures that all TMF filing is complete and up to date • Participates in, and presents at internal, Sponsor, third-party, and investigator meetings • Plans for and creates necessary documentation to support internal and external audits; participates in such audits • Trains and mentors data management staff • Prepares input for, and participates in proposal bid defense meetings • Maintains proficiency in Data Management systems and processes through regular training • Performs other work related duties as assigned

Role Description Estamos em busca de um(a) profissional especialista em MDM (Master Data Management / Gestão de Dados Mestres) para atuar em um ecossistema focado em garantir a construção e evolução da “versão única da verdade” (Golden Record), permitindo que dados corporativos sejam distribuídos, consumidos e atualizados em tempo real entre diferentes sistemas da empresa, como CRM, ERP, e-commerce, RH e demais plataformas. - Ferramentas imprescindíveis: - EBX5 - Precisly Data360 Analyze - APIs do ecossistema MDM - Principais responsabilidades e conhecimentos: - Integrações via APIs no ecossistema MDM - APIs de Consumo (Inbound / Read) - Permitem que outros sistemas consultem o dado mestre já limpo e consolidado. - Exemplo: O CRM consulta a API do MDM para buscar o endereço atualizado e validado de um cliente utilizando CPF/CNPJ como chave. - APIs de Ingestão/Escrita (Outbound / Write) - Permitem que os sistemas de origem enviem novos dados ou atualizações para que o MDM realize processos de higienização, validação, match e merge. - Exemplo: Um e-commerce envia um novo cadastro de cliente para o MDM avaliar se o registro já existe ou se é um novo cadastro. - APIs de Governança e Workflow - Integração do MDM com ferramentas de BPM (Business Process Management) ou processos que exigem aprovação humana (Data Stewardship), principalmente em casos de duplicidades ou inconsistências. - Conhecimento em padrões arquiteturais de integração MDM - Modelo Síncrono (REST / GraphQL) - Utilizado para consultas pontuais onde o sistema precisa de uma resposta imediata. - Exemplo: Validação de cadastro de fornecedor em tempo real durante o preenchimento no ERP. - Tecnologias: - REST/JSON - GraphQL (permitindo que o sistema cliente escolha exatamente quais atributos do Golden Record deseja consumir, evitando overfetching de dados complexos) - Modelo Assíncrono / Event-Driven Architecture - Essencial para sincronização em massa e atualização em tempo real de grandes volumes de dados, sem impactar os sistemas. - Exemplo: Quando o MDM consolida um novo Golden Record de produto, ele publica um evento (ex.: ProductUpdated) para que sistemas como e-commerce e ERP atualizem suas bases locais. - Tecnologias: - Mensageria e streaming de dados - Apache Kafka - RabbitMQ - Azure Event Grid - Experiência com desafios de integração de APIs MDM - Latência - O MDM trabalha com regras complexas de matching (sobreposição de dados e lógica fuzzy), exigindo APIs síncronas otimizadas para não impactar a experiência do usuário. - Idempotência - Garantir que o envio duplicado de uma mesma requisição não gere duplicidades ou comprometa o histórico do dado mestre. - Controle de Versão - Gerenciar a evolução dos modelos de dados mestres, considerando novos campos de governança, mudanças regulatórias como LGPD e garantindo que integrações legadas não sejam impactadas. Se você possui experiência nesse ecossistema e quer atuar em projetos estratégicos de dados, queremos conversar com você! 🚀