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.
We are looking for a Senior Data Engineer to help build scalable, reliable, and reusable data solutions. In this role, you will focus on industrializing data pipelines, strengthening data contracts, and delivering high-quality analytical data to support rule compliance.
You will play a key role in evolving the data infrastructure, replacing interim solutions with production-ready pipelines, and enabling efficient onboarding of new countries and business segments.
Responsibilities
- Industrialize and optimize dbt pipelines, migrating data workflows from DuckDB to PostgreSQL and retiring interim PowerQuery solutions.
- Own the versioning of scope and constraints, ensuring consistency, traceability, and reliability across data processes.
- Define and maintain data contracts with Optim-core, ensuring the availability and quality of analytical data required for rule compliance.
- Build reusable and scalable onboarding processes to support the expansion into new countries and business segments.
- Develop and maintain data transformation workflows using Python, SQL, dbt, and PostgreSQL.
- Contribute to data architecture decisions, pipeline reliability, and engineering best practices.
- Collaborate with cross-functional teams to ensure data solutions meet business and technical requirements.
Requirements for this challenge
- Strong experience in software engineering, with a focus on data engineering or data-intensive applications.
- Proficiency in Python and SQL.
- Hands-on experience with dbt and building and maintaining data transformation pipelines.
- Experience working with DuckDB and PostgreSQL, including data migration and query optimization.
- Experience with Azure cloud environments.
- Understanding of data modeling, data quality, versioning, and data contracts.
- Ability to design reusable solutions that support scalability and maintainability.
- Strong analytical and problem-solving skills.
- Excellent communication and collaboration skills, with the ability to translate business needs into reliable technical solutions.
Nice to Have
- Experience migrating data workflows from interim tools to production-ready architectures.
- Familiarity with data governance, lineage, and data quality practices.
- Experience building reusable data processes for multiple countries, markets, or business segments.
- Experience integrating analytical data pipelines with downstream platforms or optimization engines.
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