Mid-level Data Engineer

This is a fully remote position, open to applicants anywhere in the world.

📋 Description

• Proactively assist in defining requirements for the IT/Data infrastructure sector by providing technical analysis of proposed solutions and alternatives, while evaluating their impacts on performance, cost, scalability, and integration with the existing architecture;

• Approach tasks with a critical mindset, proposing enhancements and identifying technical risks in alignment with guidelines established by the senior team and corporate architecture;

• Engage in the design and implementation of medium-complexity data architectures, adhering to the standards and guidelines set by corporate architecture;

• Work collaboratively with both technical and non-technical teams, simplifying complex concepts into understandable language to promote alignment and informed decision-making;

• Contribute to project success by anticipating requirements, supporting other departments, and participating in resolving technical disagreements with a focus on results and professionalism;

• Collaborate in defining and extracting data from various sources for incorporation into Big Data platforms, ensuring compliance with established standards;

• Assist in the modeling and organization of data structures to guarantee they are suitable, accessible, and available for consumption, ensuring consistency between operational data and the analytical models needed;

• Play an active role in projects related to data and system integration, implementing medium-complexity solutions while ensuring adherence to defined architectural standards;

• Support the technical design of solutions, engage in the evolution of the existing architecture, and work on the maintenance and continuous improvement of the systems for which you are responsible.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Information Systems, Systems Analysis and Development, or related disciplines;

• Hands-on experience in developing and maintaining data pipelines;

• Strong proficiency in Python for ETL, data manipulation, and APIs (Pandas, NumPy, PySpark);

• Practical experience with Spark and/or Kafka;

• Understanding of batch and streaming processing;

• Knowledge of Data Lake, Lakehouse, and Data Warehouse concepts;

• Proficient in SQL with experience in relational databases;

• Basic understanding of NoSQL databases;

• Familiarity with DataOps, versioning, and pipeline monitoring;

• Practical experience applying agile methodologies (Scrum, Kanban).

🏝️ Benefits

• Health insurance and Dental plan

• Wellhub (Gympass)

• Commuter allowance (Vale Transporte)

• Meal and food vouchers

• Domo School (learning platform) and partnerships with educational institutions

• Private pension plan

• Life insurance

• Day off

• Extended maternity and paternity leave