At CI&T, we combine human expertise with AI to build scalable and innovative technology solutions for global clients. We are looking for a Senior Data Engineer with strong experience in Azure cloud, SQL, Python, Data Warehouse, and modern data engineering practices to join our international team.

This role is ideal for professionals who enjoy working with scalable data pipelines, cloud-based data platforms, data quality, governance, and analytics enablement in complex enterprise environments.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines in Azure environments.
• Build and optimize Data Lake and Data Warehouse solutions to support analytics and business intelligence initiatives.
• Develop and maintain data integration and orchestration pipelines using Azure Data Factory or similar tools.
• Implement data quality validation, monitoring, and cleansing processes to ensure reliable and trustworthy data.
• Create and maintain dimensional data models (Star Schema), including SCD Type 1 and Type 2 strategies.
• Develop Python-based integrations and automations, including REST API consumption and data transformation workflows.
• Implement CI/CD pipelines for data solutions and support automated deployment processes.
• Apply Data Governance best practices, including data lineage, cataloging, access control, and data ownership.
• Collaborate with international stakeholders, analysts, data scientists, and engineering teams to deliver high-quality data solutions.
• Contribute to performance optimization and FinOps initiatives for cloud-based data platforms.

Required Qualifications

• Advanced / Fluent English (C1 or higher).
• Experience working with international clients or global projects.
• Strong experience with Azure cloud services, including: Azure Data Factory (ADF), ADLS Gen2, Azure SQL Database,  Azure Functions, Azure Key Vault,  Azure Logic Apps
• Advanced knowledge of SQL / T-SQL, including: CTEs, Window Functions,  MERGE statements,  Stored Procedures,  Change detection and incremental loading strategies
• Strong experience with Python for: Data transformation, REST API integrations, JSON processing, Parquet generation, Error handling and retry patterns
• Solid understanding of Data Lake, Data Warehouse, and dimensional modeling concepts.
• Experience implementing Data Quality practices, such as completeness checks, referential integrity validation, and anomaly detection.
• Familiarity with Git and CI/CD pipelines for data projects.
• Understanding of Data Governance principles, including lineage, cataloging, security, and access management.

Nice to Have

• Experience with Apache Spark / PySpark.
• Knowledge of Azure DevOps or GitHub Actions for DataOps and CI/CD.
• Experience with cloud-based modern data stacks.
• Familiarity with FinOps practices applied to data platforms.
• Experience with multi-entity or multi-source enterprise data environments.
• Knowledge of Data Catalog and Lineage tools.

What You’ll Find

• Challenging projects in large-scale enterprise data environments.
• Opportunity to work with modern Azure data technologies and cloud-native architectures.
• Collaborative and multicultural teams.
• Continuous learning, technical growth, and participation in strategic data transformation initiatives.

If you are passionate about Azure, SQL, Python, scalable data pipelines, and modern Data Engineering practices, we would love to hear from you!