Hand Talk

Data Engineer

• Projetar, construir e fazer a manutenção das Pipelines de Dados escaláveis e eficientes;
• Fazer a manutenção da infraestrutura de dados utilizando Terraform para suportar a operação das pipelines;
• Garantir a observabilidade, qualidade e confiabilidade dos dados para os nossos clientes internos e externos;
• Automatizar processos de ingestão, transformação e orquestração sempre em alinhamento com o stakeholder para garantir a entrega de dados de forma eficiente;
• Atuar como o principal embaixador da cultura de dados dentro da Hand Talk.
• Colaborar com cientistas de dados, engenheiros de software, área de produtos e comercial para um fluxo integrado de dados.

Engenheiro de Dados Pleno – Mid-level Data Engineer

Data Scientist

• Hands-on work on Data Science projects, preferably with experience in Computer Vision or NLP;
• Strong command of fundamental machine learning concepts (proper data splitting, regularization, hyperparameter tuning);
• Ability to define and compute performance metrics (Accuracy, Precision, Recall, F1-Score) and optimize inference time for real-time operation;
• Practical experience using version control (Git) and Scrum ceremonies;
• Strong knowledge of Python for data manipulation, feature extraction, and model training;
• Practical knowledge of JavaScript/TypeScript for running and integrating models in the frontend;
• Experience with Deep Learning frameworks (TensorFlow) and Computer Vision (integration of the MediaPipe library combined with OpenCV);
• Basic system architecture knowledge and the ability to package simple applications in Docker containers for delivery to Engineering.

Mid-level Data Scientist

• Define the team’s technical priorities, translating the Head of Data Engineering’s business vision into actionable technical requirements;
• Mentorship and Code Review: Raise the team’s technical standard through rigorous code reviews and continuous mentoring of data engineers;
• Governance and Standards: Establish Data Quality standards, pipeline observability, and data lineage documentation;
• Infrastructure Decisions: Lead the Infrastructure-as-Code strategy (Terraform), ensuring consistent development, staging, and production environments;
• Data Culture: Promote a data-driven culture and platform adoption by eliminating manual processes and silos;

Data Engineer Lead – Tech Lead, Data Engineering

• Design and run AI experiments
• Develop and train advanced models
• Apply state-of-the-art techniques
• Contribute to research direction
• Partner with engineering to deploy models to production
• Analyze and optimize model performance

AI Data Scientist

QA Automation Engineer

• Analyzing workflows across global teams to identify automation opportunities using generative and traditional AI.
• Developing and implementing automations that connect our tool ecosystem (GCP and AWS clouds, Notion, CRM, Jira, GitHub, Google and Microsoft Workspace) with LLMs and AI agents.
• Acting as the steward of internal AI productivity tools, ensuring they are user-friendly for non-technical users and deliver real ROI.
• Enabling employees across functions to use AI tools (Prompt Engineering, agents) to maximize individual productivity.
• Ensuring all internal automations comply with global privacy and data security regulations (LGPD, GDPR).

Engenheiro de Dados Pleno – Mid-level Data Engineer

Mid-level Data Scientist

Data Engineer Lead – Tech Lead, Data Engineering

AI Data Scientist

AI Automation Engineer