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[Job-30586] Analytics Engineer / DBT Modelling Engineer

ciandt
Companyciandt
CategoryEngineering
LocationBrazil
RemoteRemote
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted27 Jul 2026
Last verified6 Aug 2026
SourceEmployer ATS (lever)
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Description
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're looking for an Analytics Engineer to help us with a project in the financial services sector focussing on their DBT Modelling, cross-domain data products and trusted analytics-ready datasets.   In this role you'll: Build and maintain DBT models for cross-domain analytics use cases Create reusable facts, dimensions and marts for analytics consumption Support cross-domain data products such as Churn, LTV, Segmentation and Customer Intelligence Implement dbt tests, source freshness checks and reconciliation logic Translate business requirements into data models and metric logic Support data quality checks and model validation Document model definitions, business rules, assumptions and lineage Work closely with analytics and domain teams to ensure datasets are fit for reporting and decisioning We need someone with these skills: Strong hands-on experience with DBT Strong SQL and Snowflake experience Experience building facts, dimensions, marts and analytics-ready data models Strong understanding of data modelling and metric design Experience implementing dbt tests, source freshness checks and data quality validations Ability to translate business requirements into trusted data models Experience working with analysts, product teams and business stakeholders Good documentation skills for model logic, metric definitions and lineage Experience working in modern data stack environments   #LI-BM2