Job Summary: We are seeking a Senior Data Engineer to lead strategic projects, design and optimize data pipelines, build multi-cloud data lakes, and innovate with automation and AI—ensuring scalable and secure solutions. Key Highlights: 1. Lead end-to-end strategic data projects. 2. Design and optimize batch and streaming data pipelines. 3. Innovate with automation and intelligent use of AI. We are looking for a Senior Data Engineer to work on strategic data projects spanning from ingestion to visualization. This professional will be responsible for designing, implementing, and optimizing batch and streaming data pipelines; supporting the construction of multi\-cloud data lakes; and ensuring solutions are scalable, secure, and aligned with business needs. We seek someone with proven hands-on experience in large-scale projects, capable of integrating diverse tools and driving innovation through automation and intelligent AI usage. Responsibilities * Design and implement layered batch and streaming data pipelines, ensuring reliability and performance; * Structure and evolve multi\-cloud data lakes, ensuring governance, security, and scalability; * Develop solutions on Databricks for distributed processing, machine learning, and integration with various data sources; * Work end-to-end: ingestion, processing, storage, modeling, and delivery for visualization (BI/Analytics); * Follow architectural standards and best practices for data engineering in hybrid and distributed environments; * Collaborate with business, data science, and product teams to transform data into strategic insights; * Implement automations using tools such as n8n and explore integrations with AI solutions to optimize processes; * Ensure data quality, observability, and reliability through pipeline monitoring, testing, and versioning; * Handle critical data-related incidents, leading root cause analysis and proposing sustainable solutions. Required Qualifications * Bachelor’s degree in Computer Engineering, Computer Science, Information Systems, or related fields; * Minimum of 10 years of experience in data engineering, with proven hands-on experience in complex projects; * Solid experience with batch and streaming pipelines (Spark, Kafka, Flink, etc.); * Experience with multi\-cloud data lakes (AWS, GCP, and/or Azure); * Hands-on experience with Databricks (PySpark, Delta Lake, MLlib, etc.) and Snowflake; * Practical experience covering the full data lifecycle—from ingestion to visualization (integration with BI tools such as Power BI, Tableau, Looker, Data Studio, Qlik, Einstein Insights); * Advanced proficiency in SQL and Python; * Experience with process automation (n8n, Airflow, Dagster, or similar); * Experience with data security and governance practices (LGPD/GDPR, access control, auditing); * Advanced English proficiency for reading, writing, and technical interaction. Nice-to-Have Qualifications * Experience in high-scale industries such as iGaming, fintechs, or e\-commerce; * Knowledge of AI tools applied to data (LLMs, AI Assistants, AutoML); * Experience with event-driven architecture for real-time data ingestion and processing; * Familiarity with dbt for data modeling and transformation; * Cloud certifications (AWS, GCP, or Azure) or Databricks certifications.