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, motivated, and experienced Data Engineer to join our team and build robust data-driven solutions for our customers. This role is pivotal in designing, developing, and maintaining scalable data infrastructure and pipelines that enable our data initiatives to thrive.

The Data Developer will be responsible for implementing and optimizing data architectures, ensuring data quality and reliability, and collaborating closely with analytics and business teams to deliver high-performance data solutions. This position requires strong technical expertise in data engineering, cloud platforms, and modern data stack technologies, combined with the ability to translate business requirements into effective technical solutions.

Responsibilities:

Data Pipeline Development: Build, optimize, and maintain scalable data pipelines and ETL/ELT processes to support analytics and business intelligence needs.
Data Architecture Implementation: implement data architectures, including data lakes, warehouses, and integration layers that support the organization's data strategy.
Data Quality & Governance: Implement data quality checks, validation processes, and monitoring systems to ensure data accuracy, consistency, and reliability.
Integration & API Development: Develop and maintain integrations between various data sources, third-party tools, and analytics platforms.
Collaboration: Work closely with Data & Analytics Managers, data scientists, and business stakeholders to understand requirements and deliver technical solutions that enable data-driven decision making.
Performance Optimization: Monitor and optimize data pipeline performance, query efficiency, and storage costs to ensure scalable and cost-effective solutions.
Documentation: Create and maintain comprehensive technical documentation for data architectures, pipelines, and processes.
Data Security: Implement security best practices and ensure compliance with data privacy regulations across all data systems.
Powered by AI: Leverage AI tools and automation to enhance data engineering workflows and productivity.

Requirements:

Experience with major Cloud Platform providers (Azure, AWS, or GCP)
Experience with data platforms Databricks or Snowflake
Good level of English B2 or above 
Experience working with international clients
Strong experience with data pipeline development and ETL/ELT processes
Proficiency with data warehousing solutions (BigQuery, Snowflake, Redshift, or similar)
Experience with SQL and at least one programming language (Python, Scala, or Java)
Understanding of data modeling and database design principles

Nice to Have:

Experience with modern data stack tools (dbt, Airflow, Fivetran, Stitch, etc.)
Experience with streaming data platforms (Kafka, Pub/Sub, Kinesis)
Experience with Docker and container orchestration (Kubernetes)
Experience with AI/ML pipeline development and MLOps
Experience with D2C initiatives and e-commerce analytics
Certifications in cloud platforms or data engineering
Experience with Infrastructure as Code (Terraform, CloudFormation)
Spanish communication (reading, writing, and speaking is mandatory)

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