Manager | Data Engineering

Description

Job Summary: Work in Data Engineering and Architecture, data modeling, pipeline construction, data governance and security, and technical leadership in data projects. Key Highlights: 1. Experience in Data Engineering and Data Architecture 2. Proficiency in Big Data and Cloud technologies 3. Technical leadership and collaboration in agile teams **Description:** Work in Data Engineering and Architecture, data modeling, and building ingestion and transformation pipelines. Component-oriented architecture with reusable components and data products. Big Data Platforms and Technologies Apache Spark, Apache Flink, Kafka, Iceberg, Kudu, Hive. DevOps and Code Productization Version control with Git. Continuous integration and deployment using DevOps pipelines (CI/CD). Automated testing and pipeline monitoring. Data Governance and Security Access control and policies using Apache Ranger. Knowledge of LGPD/GDPR and best practices for data protection. Cloud and Infrastructure Experience with cloud-based environments (AWS, Azure, GCP). Resource management and scalability of solutions. Orchestration and Monitoring Tools Airflow or similar tools. Monitoring of jobs and performance of distributed systems. Machine Learning Knowledge Integration of predictive models into data pipelines. Supporting business squads in operationalizing models. Technical leadership in data projects Experience managing data engineering teams, focusing on delivering reusable and scalable components. Working in multidisciplinary squads and agile methodologies. Building data pipelines and architecture Hands-on experience in large-scale data modeling, ingestion, transformation, and delivery. Knowledge of data product-oriented architectures and analytical platforms. Proficiency in Big Data technologies Practical experience with tools such as Apache Spark, Flink, Kafka, Iceberg, Kudu, Hive. Equivalent platforms for job orchestration. Data governance and security Implementation of access policies and data masking using tools like Apache Ranger. Ensuring compliance with data protection regulations (LGPD, GDPR). Code productization with DevOps Experience with Git version control, continuous integration (CI/CD), and DevOps pipelines for deploying solutions to production. Applying automated tests and monitoring components. Focus on operational efficiency Track record of delivering solutions that reduce rework, increase business team autonomy, and improve data process performance. 2512230202491882091