<p data-path-to-node="0">At CI&amp;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.</p><p data-path-to-node="1">With 30 years of experience in technological transformation, we accelerate innovation with expertise in Agentic SDLC, Application modernization, Data &amp; AI, Martech and Business strategy.</p><p data-path-to-node="3">We are 8,000 CI&amp;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.</p><div><p>CI&amp;T is strengthening its data practice to support a key client in the <strong>Logistics</strong> sector, where data-driven decision-making is rapidly becoming a critical competitive advantage. We are looking for a <strong>Senior BI Analyst / Engineer</strong> to join the Logistics Platform team a professional who bridges the gap between raw data and meaningful business insight, building the analytical foundations that empower teams to act with confidence and clarity.</p><p>In this role, you will be responsible for designing and maintaining analytical models and dashboards, developing advanced SQL and Python-based solutions, and actively fostering a data-driven culture across application and business teams. The ideal candidate is a self-driven, analytically sharp professional who combines technical depth with strong communication skills capable of independently engaging stakeholders onsite and offshore, translating complex business requirements into reliable, scalable analytical solutions.</p><h3>Responsibilities</h3><ul style="list-style-type: disc;"><li><strong>Analytics &amp; Visualization:</strong> Design, build, and maintain analytical models and dashboards in <strong>Power BI</strong> and <strong>Tableau</strong>, delivering clear and actionable insights on operational performance and business KPIs.</li><li><strong>Data Analysis:</strong> Analyze data to identify trends, patterns, and improvement opportunities, transforming findings into concrete recommendations that support strategic and operational decision-making.</li><li><strong>SQL &amp; Scripting:</strong> Develop complex <strong>SQL</strong> queries , including advanced use of regex and leverage <strong>Python</strong> for scripting, automation, and data processing workflows that support analytical models.</li><li><strong>Data Engineering &amp; Modeling:</strong> Adopt and promote best practices in data engineering, data modeling, and data integration, ensuring the reliability, scalability, and performance of analytical solutions end-to-end.</li><li><strong>Stakeholder Enablement:</strong> Guide application and business teams on data interpretation and usage, acting as a trusted analytical reference and actively contributing to building a data-driven decision-making culture within the team.</li><li><strong>Requirements &amp; Validation:</strong> Independent