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.

As CI&T grows, we seek a talented and motivated Mid-Level Data Engineer to join our team and contribute to building reliable data-driven solutions for our customers. This role involves developing and maintaining data pipelines and infrastructure that support our growing data initiatives.

The Mid-Level Data Developer will work alongside senior engineers and analytics teams to implement data solutions, ensure data quality, and help translate business requirements into technical deliverables. This position requires solid technical foundations in data engineering and cloud technologies, along with a collaborative mindset and eagerness to grow.

Responsibilities:
Data Pipeline Development: Build and maintain data pipelines and ETL/ELT processes to support analytics and business intelligence needs, under the guidance of senior engineers.
Data Architecture Support: Assist in implementing data architectures, including data lakes, warehouses, and integration layers aligned with the organization's data strategy.
Data Quality & Governance: Apply data quality checks and validation processes to ensure data accuracy, consistency, and reliability.
Integration & API Development: Support the development and maintenance of integrations between data sources, third-party tools, and analytics platforms.
Collaboration: Work with Data & Analytics Managers, data scientists, and business stakeholders to understand requirements and contribute to technical solutions that enable data-driven decision making.
Performance Optimization: Assist in monitoring and optimizing data pipeline performance and query efficiency.
Documentation: Contribute to technical documentation for data architectures, pipelines, and processes.
Data Security: Apply security best practices and support compliance with data privacy regulations.
Powered by AI: Leverage AI tools and automation to enhance data engineering workflows and productivity.

Requirements:
Experience with at least one major Cloud Platform (Azure, AWS, or GCP)
Familiarity with data platforms such as Databricks or Snowflake
Good level of English — B2 or above
Experience or exposure to working with international teams or clients
Solid experience with data pipeline development and ETL/ELT processes
Working knowledge of data warehousing solutions (BigQuery, Snowflake, Redshift, or similar)
Proficiency with SQL and at least one programming language (Python, Scala, or Java)
Basic understanding of data modeling and database design principles

Nice to Have:
Experience with modern data stack tools (dbt, Airflow, Fivetran, Stitch, etc.)
Cloud or data engineering certifications
Familiarity with Infrastructure as Code (Terraform, CloudFormation)
Spanish communication skills (reading, writing, and speaking)

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