Role Description Estamos em busca de um Arquiteto de Dados (SQL Server) para se juntar à nossa equipe dinâmica. O profissional ideal será responsável por projetar, implementar e manter a arquitetura de dados de acordo com as necessidades da nossa empresa. O candidato deve ter experiência comprovada na criação e manutenção de diagramas físicos e lógicos, alinhando-se às regras de negócio e melhores práticas. Responsabilidades: - Desenvolver e manter diagramas físicos e lógicos de banco de dados conforme as necessidades da regra de negócio. - Criar e gerenciar objetos de banco de dados, incluindo tabelas, índices, visões, procedimentos armazenados e funções conforme os requisitos do negócio. - Trabalhar em estreita colaboração com a equipe de desenvolvimento. Qualifications - Experiência sólida como Arquiteto de Dados ou em funções similares, com foco específico em SQL Server. - Expertise na criação e manutenção de diagramas físicos e lógicos de banco de dados. - Proficiência em T-SQL e capacidade comprovada para escrever e otimizar consultas complexas. - Experiência anterior em fábricas de software, com um bom entendimento dos processos e metodologias ágeis. - Conhecimento aprofundado de modelagem de dados e design de banco de dados. - Habilidade para traduzir requisitos de negócio em soluções técnicas eficazes. - Boa capacidade de comunicação e trabalho em equipe. Requirements - Certificações relevantes em SQL Server ou áreas relacionadas. - Experiência com ferramentas de ETL e integração de dados. - Conhecimento em tecnologias complementares como BI e Data Warehousing. Benefits - Contratação PJ. - Valor fixo; 10 dias de ausência remunerada. - Plano de Saúde Amil: S380 R$ 419,00, S580 R$ 518,97, S750 R$ 660,51. - Plataforma Boon, que oferece os seguintes benefícios: - Telemedicina 24h, com diversas especialidades; - Psicoterapia online e apoio em saúde mental; - Orientação social, jurídica e financeira; - Programas de cuidado para gestantes e pessoas com doenças crônicas; - Atendimento nutricional online; - Comunidades de apoio com acompanhamento de enfermeiras. - TotalPass e WellHub: Cuide do corpo e da mente com acesso a diversas academias e estúdios pelo Brasil. - OnHappy: Acesso a descontos exclusivos e condições especiais para viagens. - Educação e Carreira: Parceria com a Open English 100% custeado pela empresa (conforme disponibilidade); Trilhas de desenvolvimento disponibilizado no portal do Extremer. - Serviços de bem-estar nos escritórios, como: - Manicure - Barbearia - Massagem - Cabelereiro

• Define and maintain enterprise-wide data architecture, including conceptual, logical, and physical data models • Establish data standards, architecture principles, and best practices • Develop and evolve the organization’s data strategy aligned to business objectives • Lead migration and modernization of on-premises Oracle platforms to OCI and Azure • Architect scalable, resilient solutions using Azure SQL Database, SQL Server, Elastic Pools, and Cosmos DB • Drive adoption of cloud-native and hybrid data design patterns • Design and oversee data pipelines using Azure Data Factory and modern ETL/ELT frameworks • Enable efficient data ingestion, transformation, and delivery across operational and analytical systems • Ensure reusability and scalability of data services and pipelines • Define and implement strategies for partitioning, indexing, and query optimization • Ensure high availability, disaster recovery, and backup architectures • Monitor and optimize performance, cost, and reliability across environments • Establish and enforce enterprise data governance, data quality, and security frameworks • Ensure compliance with regulatory and organizational standards • Promote data stewardship and ownership across the organization • Evaluate emerging technologies and recommend improvements to the data ecosystem • Provide architectural guidance and mentorship to data engineers, DBAs, and developers • Foster a culture of innovation and continuous improvement • Partner with business leaders, analytics teams, and application owners to align data solutions with business needs • Translate complex technical concepts into actionable business insights • Support enterprise initiatives involving analytics, reporting, and AI/ML readiness

MongoDB is building a world-class team in North America to create tooling that helps customers modernize their applications and migrate their data from legacy relational databases to MongoDB in real-time. As companies modernise legacy workloads and data ecosystems, they are increasingly drawn to the flexibility and scalability of the document model. The tools developed by the Code Generation and Data Migration team are critical in this journey, helping customers with schema modeling, code generation, initial data loads, and continuous data synchronization. We're looking for a Software Engineer with a strong background in computer science fundamentals, systems design, experience in the Java ecosystem, streaming systems, and data-intensive applications to join our engineering team. In this role, you will be instrumental in designing, building, and optimizing the underlying data structures, algorithms, and database interactions that power our generative AI platform, code generation and migration tools. This involves crafting sophisticated orchestration layers, robust integration points, and high-performance data systems that seamlessly connect and leverage advanced AI capabilities for code generation and building a sophisticated data migration suite using a modern technology stack, which includes Java, Spring Boot, Kafka, Debezium, and React.You will work on critical components that ensure the scalability, efficiency, and reliability of our services, collaborating closely with AI researchers, product management and other engineers to design and implement cutting-edge products that solve complex customer challenges. This role will be based out of Washington, Oregon, or California. The ideal candidate for this role will have - 2+ years of engineering experience in backend systems, distributed systems, or core platform development - Experience in one or several of Java, Rust, C/C++, and/or Python, with a strong understanding of systems-level programming, memory management, and performance tuning - Experience with streaming data platforms such as Apache Kafka and Change Data Capture (CDC) tools like Debezium - Experience with relational data modeling and hands-on experience with at least one SQL database (Postgres, MySQL, etc) - Exposure to client-side technologies such as JavaScript and React is a plus - Good understanding of algorithms, data structures and their time and space complexity - Curiosity, a positive attitude, and a drive to continue learning - Excellent verbal and written communication skills Nice to Have - Familiarity with cloud-native distributed systems (e.g., Kubernetes) - Experience with NoSQL databases and understanding of their trade-offs is great, but not required. We'll teach you NoSQL - Contributions to relevant open-source projects Position Expectations - Contribute high-quality, well-tested backend code to the data migration engine and core components of our generative AI orchestration platform - Collaborate effectively with Product Management, AI researchers and machine learning engineers and designers to build and deliver on the product roadmap - Work to develop robust and efficient backend services that orchestrate AI functionalities - Identify and address performance bottlenecks and architectural challenges in our systems, particularly within data flow and orchestration - Participate actively in code reviews to enforce best practices and patterns - Help troubleshoot and resolve complex technical issues in our distributed systems - Give and solicit feedback on technical design documents and pull requests - Perform tasks related to process such as CI/CD, quality, testing, etc Success MeasuresWithin the first three months, you will have: - Familiarize yourself with the MongoDB database and aggregation language - Familiarize yourself with the backend tech stack including Java, Spring Boot, and Kafka - Set up software development infrastructure (tech stack, build tools, etc) to enable development using the relevant tech stacks - Started collaborating with your peers and contributed to code reviews. Within six months, you will have: - Familiarised yourself with the rest of our the application modernization tool stack - Delivered at least one large scale feature that spans the entire tech stack - Reviewed and contributed to scope and technical design documents Within 12 months, you will have: - Become a key contributor to our backend stack, capable of taking on complex features independently - Helped recruit and interview new members of the team - Collaborated effectively with other teams at MongoDB on cross-functional projects About MongoDBMongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure. With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software. Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world! MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter. MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Req ID: 4263333160 MongoDB’s base salary range for this role is posted below. Compensation at the time of offer is unique to each candidate and based on a variety of factors such as skill set, experience, qualifications, and work location. Salary is one part of MongoDB’s total compensation and benefits package. Other benefits for eligible employees may include: equity, participation in the employee stock purchase program, flexible paid time off, 20 weeks fully-paid gender-neutral parental leave, fertility and adoption assistance, 401(k) plan, mental health counseling, access to transgender-inclusive health insurance coverage, and health benefits offerings. Please note, the base salary range listed below and the benefits in this paragraph are only applicable to U.S.-based candidates. MongoDB’s base salary range for this role in the U.S. is: $109,000—$215,000 USD

• Support end-to-end data migration efforts between legacy and target systems • Extract, map, transform, and load (ETL) data according to defined business and technical requirements • Document data mapping, transformation rules, and migration logic • Validate migrated data to ensure completeness, accuracy, and consistency • Analyze and identify data inconsistencies, duplicates, and errors in existing systems • Perform data cleanup activities to standardize and enrich datasets • Implement data quality checks, validation rules, and monitoring processes • Collaborate with business teams to define data standards and governance practices • Investigate and troubleshoot data discrepancies across systems • Create reports and dashboards to highlight data quality metrics • Work closely with IT, business analysts, and functional teams to understand data requirements