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Brasil
Remote only
At CI&T, we help large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions.
With 30 years of experience in technological transformation, we accelerate innovation with expertise in Agentic SDLC, Application modernization, Data & AI, Martech and Business strategy.
We are 8,000 CI&Ters across more than 25 countries, collaborating to build solutions with real impact. AI is already part of how we work, evolve, and innovate every day.
At CI&T, we are looking for a talented and experienced Data Engineer to join our team and help build scalable, high-performance data solutions for global clients.
In this role, you will be responsible for designing, developing, and maintaining modern data pipelines and cloud-based data platforms that enable analytics, reporting, and data-driven decision-making. You will collaborate with cross-functional teams, ensuring data quality, reliability, and performance while implementing best practices in Data Engineering.
Design, develop, and maintain scalable ETL/ELT pipelines and data integration processes.
Build and optimize cloud-based data architectures to support analytics and business intelligence initiatives.
Ensure data quality, consistency, governance, and reliability through validation, monitoring, and automated quality checks.
Develop integrations between multiple data sources, APIs, and third-party platforms.
Collaborate with Data & Analytics Managers, Data Scientists, and business stakeholders to translate business requirements into technical solutions.
Monitor and optimize data pipeline performance, query efficiency, and infrastructure costs.
Create and maintain technical documentation for data architectures, pipelines, and engineering processes.
Implement data security best practices and support compliance with data privacy standards.
Leverage AI-powered tools and automation to improve engineering productivity and development workflows.
Advanced English (B2 or higher).
Experience working with international clients.
Strong experience in Data Engineering and ETL/ELT pipeline development.
Hands-on experience with Python and SQL.
Experience with Databricks and PySpark.
Experience with modern data warehouse platforms such as BigQuery, Snowflake, Redshift, or similar.
Solid understanding of data modeling, database design, and data architecture principles.
Ability to design scalable, reliable, and maintainable data solutions.
Experience with cloud platforms such as AWS, Azure, or GCP.
Experience with modern Data Stack tools, including dbt, Airflow, Fivetran, Stitch, or similar.
Experience with streaming technologies such as Kafka, Pub/Sub, or Kinesis.
Knowledge of data visualization platforms such as Tableau or Looker.
Experience with Docker and container orchestration using Kubernetes.
Familiarity with AI/ML pipelines and MLOps concepts.
Experience with Infrastructure as Code (Terraform, CloudFormation).
Cloud or Data Engineering certifications.
Experience designing scalable database architectures.
If you are passionate about Data Engineering, modern cloud technologies, and building scalable data solutions in a collaborative global environment, we'd love to hear from you!
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