Senior Data Engineer – Databricks

• Develop and maintain data pipelines
• Integrate and transform data from APIs, relational databases, files, and other sources
• Lead the design and development of robust data pipelines
• Collaborate with business and analytics teams to understand data requirements
• Collaborate with data scientists, analysts, and platform engineers
• Ensure the quality, reliability, security, and governance of ingested data
• Follow modern DataOps practices such as code versioning, data tests, and CI/CD
• Document data engineering processes and best practices
• Provide technical guidance and mentor peers
• Deliver high-quality data solutions aligned with organizational strategic needs

• Proven experience in building and managing large-scale data pipelines in Databricks (PySpark, Delta Lake, SQL)
• Strong programming skills in Python and SQL for data processing and transformation
• Deep understanding of ETL/ELT frameworks, data warehousing, and distributed data processing
• Hands-on experience with modern DataOps practices, including version control (Git), CI/CD pipelines, automated testing, and infrastructure-as-code
• Familiarity with cloud platforms (AWS, Azure, or GCP) and related data services
• Strong problem-solving skills to troubleshoot performance, scalability, and reliability issues
• Proficiency in Git
• Advanced English is essential

• Health and dental insurance
• Meal and food allowance
• Childcare assistance
• Extended paternity leave
• Partnership with gyms and health and wellness professionals via Wellhub (Gympass) TotalPass
• Profit Sharing and Results Participation (PLR)
• Life insurance
• Continuous learning platform (CI&T University)
• Discount club
• Free online platform dedicated to physical, mental, and overall well-being
• Pregnancy and responsible parenting course
• Partnerships with online learning platforms
• Language learning platform
• Health and well-being team, inclusion specialists, and affinity groups
• Support and accommodations for people with disabilities during the selection process