• Design, build, and maintain reusable feature datasets that support machine learning use cases including personalization, engagement, risk prediction, churn modeling, recommendation systems, and experimentation. • Establish self-service foundations that streamline and democratize dataset creation across the data organization. • Partner with Data Scientists to translate modeling requirements into production-ready feature pipelines, supporting the full model lifecycle from exploration to deployment. • Identify source data, transformations, and historical windows needed for feature engineering. Help define and build shared, reusable feature definitions across models rather than one-off datasets. • Balance features freshness, correctness, latency, and computational efficiency when designing data pipelines. • Build datasets that support both historical model training and future production inference. • Design and implement batch and streaming pipelines that transform raw healthcare, behavioral, product, and operational data into trusted ML-ready datasets. • Build reliable data processing systems using Python, SQL, Spark, and modern cloud data platforms. • Optimize large-scale distributed processing for performance, scalability, and cost. • Design data pipelines that are modular, testable, observable, and easy to evolve as product requirements change. • Ensure data quality through testing, anomaly detection, schema validation, and pipeline monitoring. • Partner with platform teams to support near real-time feature generation where appropriate. • Improve reproducibility by standardizing feature computation across experimentation and production. • Support rapid experimentation without sacrificing long-term maintainability. • Establish engineering standards for correctness, documentation, and maintainability. • Familiarity with feature stores or feature management platforms. • Familiarity with model training pipelines and MLOps workflows.

Role Description Estamos em busca de um(a) Engenheiro(a) de Dados Pleno para integrar a equipe. Nesta função, o profissional será responsável por transformar requisitos funcionais e não funcionais dos produtos em componentes de software, em conformidade com as especificações, diretrizes de arquitetura e padrões de codificação. A posição tem foco no desenvolvimento e evolução de processos de ETL, construção e otimização de pipelines de dados e no suporte técnico às equipes internas. - Transformar requisitos funcionais e não funcionais dos produtos em componentes de software. - Projetar, desenvolver (codificar) e testar componentes de software. - Automatizar testes unitários e documentar o código de acordo com os padrões estabelecidos. - Aplicar protocolos de gerenciamento de configuração de software. - Corrigir defeitos de código identificados durante os testes. - Desenvolver e evoluir processos de ETL. - Construir e otimizar pipelines de dados. - Fornecer suporte técnico às equipes internas de Dados, Negócios e Tecnologia. Qualifications - Experiência em Engenharia de Dados ou áreas relacionadas. - Conhecimento em: - Python; - GitHub; - DBT; - SQL; - PostgreSQL; - Apache Airflow; - Docker; - Serviços da AWS. - Experiência com versionamento de código. - Conhecimento em DataHub e Kubernetes será considerado um diferencial. Company Description - Local de atuação: São Paulo/SP – Brasil. - Modelo de trabalho: Remoto (necessário residir no Brasil).

Role Description Estamos em busca de um Engenheiro de Dados Sênior para integrar nosso projeto de IA, focado em desenvolver uma arquitetura de dados e IA on premise, com modelos rodando em cloud. Este projeto visa alcançar metas até 2026, garantindo governança e infraestrutura escalável. - Desenvolvimento e evolução de processos de ETL. - Construção e otimização de pipelines de dados. - Apoio técnico à equipe interna, incluindo dados, negócios e tecnologia. Qualifications - Graduação em Ciência da Computação, Engenharia ou área relacionada. Requirements - Experiência mínima de 3 anos em engenharia de dados. - Conhecimento em Python, GitHub, SQL, DBT, Postgres, Airflow, Docker e serviços AWS. - Diferenciais: Experiência com Datahub e Kubernetes. Benefits - Localidade: São Paulo, SP - Nível de experiência: Sênior - Modelo de trabalho: Remoto

Role Description Harbor is looking for detail-oriented and committed Data Quality Professionals (DQPs) to join our growing Managed Services team. As a DQP, you’ll play a key role in helping our clients maintain accurate, high-quality data that supports their business development and relationship management efforts. This is a remote position ideal for individuals who thrive in a structured, flexible work environment with a strong emphasis on quality, accuracy, and independence. Our team is distributed across multiple states, working from home offices with the support of experienced Quality Specialists and Client Managers. Join our team as a Data Quality Professional and make a real impact by delivering accurate, high-quality data that helps our clients succeed. Hourly Pay Rate: $15.00 per hour Responsibilities: - Log in and complete assigned work each week according to deadlines - Review and update client data accurately based on provided Style Guides - Research and validate information using internal and external data sources - Resolve data discrepancies and merge duplicate records - Follow standardized procedures for general data clean-up projects - Exercise sound judgment in determining accurate data - Review audit feedback weekly, correcting any errors and implementing coaching guidance - Communicate issues or blockers proactively with your team - Attend and contribute to team meetings Qualifications - You bring 3+ years of professional work experience or similar, ideally in a detail-driven role - You follow directions carefully and execute tasks with high accuracy - You have strong communication and collaboration skills, especially in virtual settings - You are technically proficient and comfortable using software tools and systems - You are self-motivated, organized, and able to manage your time independently - You take pride in your work and are committed to delivering a high standard of quality - You maintain confidentiality and demonstrate discretion when handling sensitive information Requirements - Reliable, high-speed internet connection - A quiet, dedicated workspace free from distractions during work hours Core Competencies - Demonstration of Firm Values: Models professionalism, respect, and integrity in day-to-day performance and communication. - Collaboration & Teamwork / Developing Self and Others: Builds strong relationships with teammates and managers; acts as a reliable and supportive resource. - Commitment to Client Service: Responds effectively to client needs under the guidance of the Client Manager and team leads. - Execution of Work / Operational Competence: Exhibits proficiency in executing data-related tasks with a strong understanding of internal processes and tools. - Effective Communication: Demonstrates clear, professional communication and effectively summarizes data findings and task status. Key Skills - Patience, focus, and a proactive mindset - Exceptional attention to detail and quality - Strong problem-solving and research skills - Excellent written and verbal communication - Comfortable collaborating across a distributed, remote team - A growth mindset and eagerness to improve and learn Benefits - Work from home in a fully remote position with a flexible schedule - No dress code – wear what’s comfortable - No commute – save time and money - Supportive team environment with accessible Quality Specialists and Client Managers - Opportunities for advancement – we promote internally and recognize talent