DATA ENGINEER

Data Engineer - Participate in the technical architecture definition together with the architecture team, incorporating technical detailing, documentation. Enforce the data governance standards set by the company. Assistance in the understanding and development of activities for younger team members. Actively participate in sprint rituals and others, collaborating to achieve the desired results within the deadline provided by the planning. Collaborate in technical decisions about the evolution of software products, including performing Code Reviews. Develop Data Warehouse, Data Lake, and Lakehouse structures. Develop, deploy, and update data pipelines providing maintenance and technical support to systems/applications as per business requirements. Ensure the construction of codes with quality and free of structural defects. Apply unit and integrated tests. Develop scripts and update routines applying CI/CD techniques. Develop Data Products and APIs for data consumption. Design the database structure using good modeling practices following the standards defined for the project. Create and modify pipelines (ETL/ELT), changing processing, coding and other elements avoiding impacts on other components / software. Education and experience 04+ years of relevant experience in the area . Higher Education in Systems Analysis and Related Materials. Hard Skills Technical background in Microsoft and Linux platforms . Advanced knowledge of containers (Docker , others). Knowledge of Kubernetes (deployment, job, ingress, RBAC and key features). Knowledge about cloud computing. Deep knowledge of distributed systems. Knowledge of the main types of software architecture. Knowledge of the main types of big data architecture and their respective components; Data modeling (Relational - MER, Dimensional - Star Schema and Snowflake). Data format (JSON, XML, CSV, Parquet, Iceberg, Avro among others). Knowledge of design patterns. Differentiating knowledge in Business Intelligence tools (Qlik, PowerBI or others). Development of data pipelines using Spark (PySpark, Scala, Java, R). Knowledge in relational databases (Postgres, MySQL, SQL Server, Oracle or similar). Deep knowledge of the concepts of BIG DAT A. Knowledge about the use of ETL/ELT . Knowledge about NoSQL (Key-value, Documents, Memory, and Graphs) such as: MongoDB, Elastic, Redis, Memcache, ArangoDB, Neo4j or similar. Knowledge of messaging systems (Kafka, Rabbit and similar). Knowledge of integration tools and APIs (Restfull, gRPC, WebSockets, GraphQL). Mastery of the use of GIT, GIT Flow and tools. Knowledge of DevOps practices (in the role of developer). Software testing strategies. Full understanding of Scrum processes and ceremonies. Knowledge of good management practices in technology (ITIL among others). Differential is having solid knowledge of machine learning, deep learning, and generative AI (LLM). Advanced English. Soft Skills Organization and planning. Focus on results. Proactivity. Efficient communication. Innovative profile. Trading Ability / Flexibility. Analytical capacity. Interpersonal relationship. Systemic view.