[Job-31231] MidLevel Data Engineer, Brazil

At CI&T, we combine human expertise with AI to build scalable technology solutions for global clients. We are looking for a Mid Level Data Engineer to join our team and contribute to the development and evolution of data solutions.

This role is ideal for someone with hands-on experience building data pipelines, working with Python and SQL, and using modern development practices such as Git and CI/CD. Experience with Azure and Databricks is a plus.

Key Responsibilities

• Develop and maintain data pipelines for data ingestion, transformation, and processing.
• Build and optimize data solutions using Python and SQL.
• Work with different data sources to transform and prepare data for consumption.
• Monitor, troubleshoot, and improve data pipelines and processes.
• Use Git and CI/CD practices to support development and deployment workflows.
• Collaborate with Data Engineers, Analysts, and other stakeholders to understand data requirements and deliver effective solutions.
• Contribute to continuous improvements in data quality, performance, and reliability.

Required Qualifications

• Experience working as a Data Engineer, Data Developer, or in a similar data-focused role.
• Strong experience with Python.
• Strong knowledge of SQL.
• Hands-on experience developing and maintaining data pipelines.
• Experience with Git, GitHub, and CI/CD practices.
• Advanced/Fluent English – C1 or higher, with the ability to communicate effectively in meetings, discussions, and written communication with international stakeholders.
• Good problem-solving and analytical skills.
• Ability to work collaboratively in a global and multicultural environment.

Nice to Have

• Experience with Azure and its data services.
• Experience with Databricks.
• Knowledge of PySpark.
• Familiarity with cloud-based data platforms and modern data engineering practices.

What You’ll Find at CI&T

• Opportunity to work on data-driven transformation projects for global clients.
• Exposure to modern cloud and data technologies.
• A collaborative environment focused on continuous learning and technical growth.
• The opportunity to work on challenging data solutions and contribute to meaningful business outcomes.