Role Description The Data Entry Associate is responsible for accurately entering, updating, and maintaining information across digital systems, spreadsheets, and databases. This role is ideal for someone who is detail‑oriented, organized, and comfortable working independently in a remote environment. The position requires a high level of accuracy, consistency, and the ability to manage repetitive tasks while maintaining quality standards. In this role, the associate will support various departments by processing data, reviewing records for completeness, and ensuring information is properly formatted and stored. The ideal candidate thrives in a structured workflow, communicates clearly, and can manage deadlines without direct supervision. Training is provided, and high performers may have opportunities to grow into data quality, reporting, or operations support roles. Key Responsibilities - Enter, update, and maintain data in spreadsheets, databases, and internal systems - Review information for accuracy, completeness, and consistency - Clean, organize, and standardize data across multiple sources - Identify errors or discrepancies and correct or escalate as needed - Maintain confidentiality and follow data‑handling guidelines - Assist with generating basic reports or summaries when requested - Manage daily data entry tasks and meet productivity expectations - Support team members with administrative or data‑related tasks Qualifications - Strong attention to detail and accuracy - Fast and consistent typing skills (40+ WPM preferred) - Comfort working with spreadsheets (Excel or Google Sheets) - Ability to follow structured workflows and instructions - Strong organizational and time‑management skills - Ability to work independently in a remote environment - Reliable internet connection and computer access Requirements - Previous experience in data entry, administrative support, or similar roles - Familiarity with CRM systems or data management tools - Basic understanding of data cleaning or formatting - Experience working in remote or distributed teams Benefits - This is a fully remote position with flexible scheduling depending on business needs - The work environment is structured, supportive, and focused on accuracy and efficiency - Compensation includes a competitive hourly rate - Paid training - Opportunities for advancement into data quality, reporting, or operations roles

• Supervisar y optimizar la plataforma Denodo, definiendo buenas prácticas de desarrollo, gobierno y rendimiento. • Diseñar y apoyar nuevas integraciones de datos, asegurando su alineación con la arquitectura y estándares establecidos. • Actuar como referente técnico para el equipo en consultas relacionadas con Denodo y BigQuery. • Definir patrones de integración y optimización sobre tecnologías como Denodo, Snowflake, BigQuery, DBT y herramientas de orquestación de datos.

• Apoiar a construção, modelagem e manutenção do nosso data lake nas camadas Raw, Bronze e Silver. • Desenvolver e manter pipelines de dados robustos, escaláveis e bem documentados. • Automatizar processos de coleta, transformação, entrega e distribuição de dados internos e externos. • Garantir observabilidade, qualidade, consistência e governança dos dados. • Monitorar e otimizar o desempenho de pipelines, workloads e processos de transformação. • Trabalhar em parceria com analista, cientista de dados, engenheiro e stakeholders de produto. • Apoiar áreas de negócio com dados confiáveis para tomada de decisão. • Aplicar boas práticas de versionamento, testes e CI/CD em projetos de dados.

• Design, build, and scale robust ETL/ELT pipelines optimized for AI workloads, including RAG, fine-tuning, and batch inference. • Transform unstructured data sources such as PDFs, logs, and transcripts into structured and vectorized formats suitable for LLM consumption. • Maintain and automate the data-to-model lifecycle, ensuring AI knowledge bases remain synchronized with changing business data. • Develop and maintain real-time feature pipelines that support low-latency AI and machine learning applications. • Integrate data platforms with Kafka and other event-driven systems to enable real-time processing and AI-driven responses. • Manage and optimize Feature Stores to ensure consistency between model training and production environments. • Implement automated data quality controls and validation processes to ensure the reliability and accuracy of AI training and inference data. • Establish and maintain data lineage frameworks to provide traceability, auditability, and regulatory compliance across data workflows. • Enforce data security, privacy, and governance standards, including PII protection and compliance with industry regulations. • Manage data movement and synchronization across on-premises systems, cloud platforms, and data warehouses. • Optimize data storage and retrieval strategies for Vector Databases to support high-performance RAG and AI search workloads. • Collaborate with Data Scientists, ML Engineers, Software Engineers, and business stakeholders to deliver scalable AI data solutions.