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.
Responsibilities
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Design, develop, and maintain scalable ETL/ELT pipelines and data integration processes.
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Build and optimize cloud-based data architectures to support analytics and business intelligence initiatives.
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Ensure data quality, consistency, governance, and reliability through validation, monitoring, and automated quality checks.
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Develop integrations between multiple data sources, APIs, and third-party platforms.
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Collaborate with Data & Analytics Managers, Data Scientists, and business stakeholders to translate business requirements into technical solutions.
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Monitor and optimize data pipeline performance, query efficiency, and infrastructure costs.
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Create and maintain technical documentation for data architectures, pipelines, and engineering processes.
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Implement data security best practices and support compliance with data privacy standards.
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Leverage AI-powered tools and automation to improve engineering productivity and development workflows.
Required Qualifications
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Advanced English (B2 or higher).
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Experience working with international clients.
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Strong experience in Data Engineering and ETL/ELT pipeline development.
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Hands-on experience with Python and SQL.
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Experience with Databricks and PySpark.
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Experience with modern data warehouse platforms such as BigQuery, Snowflake, Redshift, or similar.
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Solid understanding of data modeling, database design, and data architecture principles.
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Ability to design scalable, reliable, and maintainable data solutions.
Nice to Have
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Experience with cloud platforms such as AWS, Azure, or GCP.
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Experience with modern Data Stack tools, including dbt, Airflow, Fivetran, Stitch, or similar.
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Experience with streaming technologies such as Kafka, Pub/Sub, or Kinesis.
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Knowledge of data visualization platforms such as Tableau or Looker.
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Experience with Docker and container orchestration using Kubernetes.
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Familiarity with AI/ML pipelines and MLOps concepts.
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Experience with Infrastructure as Code (Terraform, CloudFormation).
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Cloud or Data Engineering certifications.
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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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