Pessoa Engenheira de Dados Sênior

Senior Data Engineer This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer based in Brazil. This is a senior-level role focused on building the data foundation that enables enterprise-scale artificial intelligence to operate with reliability, context, and performance. You will be responsible for designing and evolving end-to-end data ecosystems that support analytics, machine learning, and AI-driven applications. The position goes beyond traditional data engineering, requiring a strong understanding of how data fuels LLMs, RAG systems, and intelligent agents in production environments. You will work across structured and unstructured data sources, ensuring high-quality ingestion, transformation, and availability for downstream consumption. A key part of the role is guaranteeing data governance, lineage, security, and compliance while enabling fast and scalable access to information. You will collaborate closely with AI, ML, product, and platform teams to ensure data is always reliable, well-structured, and ready for intelligent systems. This is a highly strategic role for someone who sees data as the core enabler of modern AI-powered products. Accountabilities: Design, build, and maintain scalable data pipelines across batch, near real-time, and streaming architectures. Integrate diverse data sources including APIs, databases, files, logs, and enterprise systems. Develop reliable data layers for analytics, AI applications, RAG pipelines, embeddings, and automation workflows. Implement robust processes for ingestion, transformation, modeling, validation, monitoring, and optimization of data flows. Work with structured and unstructured data, including documents, events, transactional systems, and logs. Prepare and optimize datasets for AI systems, including LLMs, semantic search, and agent-based applications. Enforce data governance practices such as lineage tracking, data contracts, versioning, and documentation. Ensure compliance with security, privacy, LGPD, anonymization, and data masking requirements. Collaborate with AI, ML, platform, and product teams to ensure timely, high-quality data delivery. Requirements: Strong experience in Data Engineering in cloud, hybrid, or enterprise environments. Advanced knowledge of SQL and Python for data processing and pipeline development. Hands-on experience with tools such as Spark, Databricks, Airflow, dbt, AWS Glue, Kafka, or equivalent. Solid understanding of data lake, lakehouse, and data warehouse architectures. Experience with ETL/ELT pipelines, orchestration, monitoring, and failure handling strategies. Knowledge of data quality practices, testing, observability, and performance optimization. Experience handling multiple data formats and complex integration scenarios. Strong understanding of data governance, security, and access control models. Experience working with distributed systems and large-scale data environments. Strong analytical thinking, organization, and attention to detail. Benefits: Cooperative contract model with competitive compensation aligned to market standards Fully remote (Anywhere Office) work flexibility BYOD support for equipment purchase or personal device usage Home office allowance via flexible benefits card (iFood Benefícios – free category) Health and wellness benefits including TotalPass, Wellhub, and healthcare platforms Additional perks such as birthday day off, benefits club, and temporary disability coverage (DIT) Continuous learning support, training, and certifications Exposure to cutting-edge AI, data, and platform engineering initiatives Collaborative and innovation-driven environment focused on impact and autonomy Jobgether