Data Engineer • Senior

Who you are

You have a strong background in data engineering with expertise in PySpark and SQL — you've developed and maintained data pipelines in cloud environments, ensuring data quality and integrity. Your experience with Azure Data Services and Databricks allows you to efficiently process and integrate data for various applications.

You are proficient in Python and understand the intricacies of data manipulation and transformation — your skills in CI/CD practices and version control with GitHub enable you to automate deployments and maintain code quality. You have a solid grasp of data modeling concepts, ensuring that your designs are scalable and performant.

You are familiar with data governance and best practices, having participated in projects that require strict adherence to data quality standards — your knowledge of data profiling techniques helps you monitor and ensure the consistency of data across systems. You thrive in collaborative environments, working closely with business teams and data scientists to deploy AI models effectively.

Desirable

Experience with DB2 and familiarity with MDM initiatives would be advantageous — your participation in AI projects and automation of data pipelines showcases your ability to innovate and improve processes. Knowledge of data lake and data warehouse architectures further enhances your profile as a data engineer.

What you'll do

In this role, you will develop and maintain ETL/ELT data pipelines in an Azure environment, utilizing Databricks for processing and integration — your contributions will ensure that data flows seamlessly to support business intelligence and analytics initiatives. You will implement CI/CD practices to automate deployments and manage versioning in GitHub, ensuring that your code is always up to date and reliable.

You will design and optimize data models to guarantee scalability, performance, and governance — your work will directly impact the quality and accessibility of data for various stakeholders. Supporting cloud migration projects will be a key responsibility, where you will ensure the security, quality, and integrity of data throughout the transition.

Collaboration is essential in this role, as you will work with business teams and data scientists to deploy AI models in a cloud environment — your ability to communicate effectively will help bridge the gap between technical and non-technical teams. You will also document processes, architectures, and best practices in data engineering, contributing to the overall knowledge base of the organization.

What we offer

CI&T provides a dynamic work environment where innovation and collaboration are at the forefront — you will be part of a team that values your contributions and encourages professional growth. We offer competitive compensation and opportunities to work on cutting-edge projects that leverage AI and data technologies.

Join us in transforming technology and making a significant impact in the financial sector — your expertise will help shape the future of data engineering at CI&T.