Where this role is available
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- Brazil, Brazil
- Brazil
Role summary by JobGrid
[Job-29647] Senior Data Engineer, Brazil at ciandt: Brazil, Brazil, Brazil; On-site; IT; Data Engineer. JobGrid adds normalized role facts, source context, and a path to the employer application page so candidates can compare the listing before applying.
- Location and workplace: Brazil, Brazil, Brazil, On-site
- Role classification: IT, Data Engineer
- Source freshness: checked by JobGrid on 2026-06-11.
- Application path: candidates continue to the employer application page with non-personal referral tags.
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.
What we're looking for
We're looking for a Senior Data Engineer with deep expertise in GCP, who can operate confidently across the platform, independently drive technical decisions, and deliver scalable, reliable data solutions in a cloud-native environment.
Required qualifications
- Strong hands-on experience as a Data Engineer working with Google Cloud Platform (GCP).
- Solid experience with BigQuery, Dataform, Cloud Functions, Dataflow, GKE, and Docker.
- Advanced programming skills in Python and SQL.
- Experience designing and maintaining end-to-end data pipelines and data processing workflows.
- Strong understanding of cloud architecture, scalability, and data engineering best practices.
- Ability to work independently, take ownership of technical solutions, and drive initiatives with minimal supervision.
- Strong problem-solving and analytical skills.
- English level: Advanced or Fluent.
Nice to have
- Experience working in agile environments.
- Knowledge of data governance, monitoring, and observability practices.
- Experience supporting analytics, reporting, or machine learning workloads.