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.
Responsibilities:
Managing the complete Data Lifecycle, from where data is generated to ETL pipelines and data enablement.
Data Architecture & Infrastructure: understanding the technical architecture/infrastructure that supports the organization's data needs, including storage, integrations, and analytics platforms.
Task Prioritization: working with technical and business teams to understand their data needs and priorities and effectively communicate the value of data initiatives. Prioritizing tasks and defining the roadmap, balancing competing demands from different stakeholders.
Data Profiling: understanding the data types, relationships, patterns, and trends to understand the data better.
Requirements Definition: collaborate with internal and external stakeholders to understand and document data requirements, ensuring they are clear, specific, and achievable, as well as how the data should be presented to consumption.
Business Process: understand the business workflows so appropriate assumptions can be made regarding sources, entities, and attributes to answer business questions.
Validation: validating the product with users to ensure it meets their needs and expectations, using data and metrics to inform decisions.
Performance Analysis: monitoring and analyzing product performance, using metrics and KPIs to assess success and metrics to track the effectiveness of data initiatives and investments, and using data-driven insights to drive continuous improvement.
Powered by AI: support incorporating AI in the team workflow to speed up performance.
Team Leadership: leading cross-functional teams, including data scientists, engineers, and analytics specialists, to develop and deliver high-quality data products. Attracting, retaining, and developing top data talents. Mentoring, training, and pursuing growth opportunities to build motivated teams.
Requirements:
-Solid experience as a Data Architect, leading teams
- Experience in either the Data Platform, Data Visualization, Salesforce Integration or Advanced Analytics space
- Experience with Azure
- Experience migrating data platform to cloud
- Experience building data platforms on-prem and in the cloud
- Experience with widely used operational tools such as Hubspot, Workday, Segment, or Braze
- Experience with project management tools
- Experience with AI/ML
- Advanced/Fluent english
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