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.

This position is responsible for designing, building, and guaranteeing the reliability of the analytics assets that drive strategic decisions and optimize business processes. The role involves engineering trusted data models and dashboards, certifying the accuracy of the insights they deliver, and setting state-of-the-art practices.

KEY RESPONSIBILITIES

- Design and/or optimize semantic models, setting Power BI data modeling and DAX standards in line with market best practices.
- Define and evolve the standardized processes established by the client's Digital & AI Factory.
- Own the transformation layer end to end, guaranteeing strong data modeling practices, data normalization, and optimal performance.
- Leverage AI-assisted tooling to accelerate delivery, and evaluate emerging technologies to keep the practice at the market state of the art.
- Act as technical expert for the Data Analytics community, reviewing semantic models, proposing solutions, and mentoring senior and mid-level analysts.
- Guarantee data accuracy through systematic validation, reconciliation against source systems, and repeatable automated testing.

REQUIREMENTS

- 8+ years of experience as a Data Analyst or in a similar role, with a record of owning business-critical analytics products end to end.
- Expert-level command of Power BI, covering semantic modeling, DAX optimization, and performance tuning.
- Expert in data manipulation and query languages, particularly SQL and Power Query / M, including diagnosing performance bottlenecks at the source.
- Strong knowledge of DBT, Databricks, or other data transformation and pipeline tools, and of engineering practices applied to Power BI (Git, PBIP, CI/CD).
- Proven track record of implementing data quality and automated testing frameworks that guarantee the accuracy of reported figures.
- Daily, critical use of AI-assisted tooling for analytics development, with the judgment to validate and correct generated output.

- Advanced English level for daily meetings and presentations.

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