Engenheiro de Dados Sênior| IA Generativa, Dados e MDM

Accountabilities: As a Senior Data Engineer, you will be responsible for designing, developing, and optimizing scalable data solutions that support AI-driven initiatives, data governance, and business intelligence. Your responsibilities will include: Developing, optimizing, and maintaining scalable data pipelines using Databricks, Spark, and PySpark; Integrating, transforming, processing, and making customer data available across large-scale environments; Building and maintaining cloud-based Big Data products, ensuring scalability, performance, reliability, and data quality; Supporting initiatives related to customer data management, Golden Record, data quality, governance, and MDM; Designing data solutions that enable Generative AI applications, autonomous agents, multi-agent systems, and intelligent workflows; Preparing and structuring data for consumption by Machine Learning models, LLMs, AI agents, and automated processes; Supporting the development of intelligent agents capable of analyzing large volumes of customer data; Identifying patterns, inconsistencies, duplicates, anomalies, and opportunities for improvement within data assets; Developing mechanisms for alerts, explainable recommendations, and data-driven decision support; Applying Analytics and Machine Learning techniques for anomaly detection, classification, clustering, and scoring; Supporting data enrichment, prioritization, and governance strategies; Exploring and implementing architectures such as RAG, autonomous agents, and intelligent workflows; Working with near real-time data processing solutions using Kafka; Supporting Machine Learning model production in Databricks through MLOps practices; Creating and maintaining CI/CD pipelines using GitHub and GitHub Actions; Ensuring engineering best practices related to quality, efficiency, maintainability, testing, and governance; Collaborating with Data, Technology, MDM, and Business teams to deliver measurable and applicable solutions; Participating in technical refinements, process analysis, and AS-IS/TO-BE documentation; Identifying technical debt and proposing continuous improvements in architecture, processes, and data solutions. Requirements: We are looking for a senior professional with strong experience in data engineering, cloud environments, and AI-driven data solutions. The ideal candidate should have: Solid experience as a Data Engineer, Senior Data Engineer, or similar role; Strong knowledge of Python for data engineering, automation, analytics, and AI solution development; Advanced SQL skills and experience working with structured data exploration; Hands-on experience with Databricks, PySpark, and Apache Spark; Proven experience building, optimizing, and maintaining scalable data pipelines; Experience working with cloud environments, preferably Azure Databricks; Knowledge or experience with Gemini and Generative AI solutions; Experience with LLMs, AI-powered applications, and intelligent data workflows; Familiarity with RAG architectures, recommendation systems, cognitive automation, and intelligent workflows; Experience applying Machine Learning techniques such as anomaly detection, classification, clustering, and scoring; Experience with near real-time data processing, preferably using Kafka; Experience deploying Machine Learning models in Databricks and applying MLOps practices; Experience with CI/CD pipelines, especially GitHub and GitHub Actions; Knowledge of data engineering best practices, version control, testing, code review, and data quality processes. Additional skills that are considered a plus: Experience working with critical data domains such as customer identity, registration, or KYC; Knowledge of data quality, governance, MDM, and Golden Record concepts; Experience with multi-agent systems, cognitive automation, or autonomous decision-making solutions; Experience working in regulated environments; Knowledge of deduplication, matching, consolidation, and customer data enrichment strategies; Experience using AI-assisted development tools, prompt engineering, or automated code review solutions. Benefits: Health and dental insurance; Meal and food allowance; Childcare assistance; Extended parental leave; Access to fitness and wellness partnerships through Wellhub and TotalPass; Profit-sharing program (PLR); Life insurance; Continuous learning platform and professional development opportunities; Discount club with partner benefits; Free online platform focused on physical, mental, and emotional well-being; Parenting and maternity support programs; Partnerships with online learning platforms; Language learning platform; Additional benefits according to company policies.