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.

Main responsibilities
- Define, build, and deliver high-quality, high-performance data pipelines in Azure (ADF, Synapse, Databricks) and, when necessary, on on-premises platforms.
- Ensure continuous support and maintenance of existing data pipelines, including proactive monitoring and handling of complex incident and problem tickets, troubleshooting failures and fixing bugs, proposing and implementing architectural and code improvements.
- Participate in the Data Validation process.
- Ensure that all systems meet the business requirements and the non-functional requirements (performance, security, privacy, GDPR/LGPD).
- Integrate up-and-coming data management and software engineering technologies into existing data structures.
- Analyze and organize raw data, ingest, transform, and make data available in data lakes and data marts.
- Collaborate directly with BI, Data Science, and Software Engineering teams to document and deliver consistent data solutions.

Requirements
- Solid experience in Azure Cloud data ecosystem (focus on ADF, Synapse, Databricks/Spark, ADLS).
- Development of reports (Reporting Services) and dashboards (Power BI).
- Experience in designing, building, and testing data pipelines (ETL/ELT), ensuring performance and reliability.
- Comfort in learning and integrating new frameworks and cloud-native technologies.
- Ability to share your knowledge with more junior team members.
- Knowledge on Microsoft SQL Server tech stack.
- Robust experience in Dimensional Modelling and Strong domain knowledge of SQL for building Data Marts and Data Warehouses.
- Experience in contributing to technical reference, assisting in defining data standards, and participating in code reviews.
- Practical experience in applying Software Engineering principles, including advanced use of Git (branches, PRs) and implementing/maintaining CI/CD for data solutions.

Nice to have
- Knowledge of unit, integration and E2E testing.
- Cloud Certification (Azure or AWS)
- Knowledge of Data Catalog and Lineage processes and tools (e.g., Azure Purview).
- Experience with Python or Scala for scripting and data process automation.
- Experience with Orchestration tools like Airflow.

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