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 Analytics Engineer to design, maintain, and evolve data models that power business intelligence and analytical solutions. In this role, you will own the layered dbt data model, enabling reliable data consumption across Power BI and downstream applications.
You will play a key role in supporting the development of a pricing engine, enhancing item categorization and price elasticity analysis, and harmonizing KPIs across regions to establish a consistent, data-driven pricing methodology.
Responsibilities
Own and evolve the layered dbt data model, ensuring reliable, consistent, and well-structured data for Power BI and downstream consumers.
Develop and maintain data transformation workflows using dbt and SQL, following best practices for modularity, testing, documentation, and maintainability.
Extend existing data models to support the pricing engine MVP, including item categorization and price elasticity analysis.
Harmonize business KPIs across regions, ensuring consistent definitions and calculations to support a common pricing methodology.
Build and optimize analytical data solutions using Databricks and Azure.
Apply Python where needed to support data processing, analysis, and automation.
Develop and maintain data models for Power BI, enabling accurate reporting and effective business insights.
Ensure data quality, consistency, and usability across analytical models and downstream applications.
Collaborate with business stakeholders, data teams, and regional teams to translate analytical requirements into scalable data solutions.
Contribute to continuous improvements in data architecture, modeling practices, and analytics engineering standards.
Requirements for this challenge
Strong experience in analytics engineering, data engineering, or a related data-focused role.
Advanced proficiency in SQL and hands-on experience with dbt.
Experience designing and maintaining layered data models for analytics and business intelligence.
Experience with Databricks and Azure data environments.
Proficiency in Python for data processing, analysis, or automation.
Experience with Power BI, particularly data modeling and preparing data for reporting and analytics.
Strong understanding of data quality, data validation, and consistent metric definitions.
Ability to translate business requirements into robust, reusable data models.
Strong analytical and problem-solving skills, with attention to detail and data accuracy.
Excellent communication and collaboration skills, including the ability to work with stakeholders across different regions.
Nice to Have
Experience supporting pricing, revenue optimization, or commercial analytics initiatives.
Knowledge of price elasticity, product categorization, and pricing performance metrics.
Experience harmonizing KPIs and business definitions across regions or markets.
Familiarity with modern data architecture and scalable analytical data platforms.
Experience with data testing, documentation, lineage, and governance practices.
Ability to balance technical modeling decisions with business priorities and analytical needs.