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.
CI&T's Data & Analytics practice is scaling its portfolio of data-driven engagements for enterprise clients, and we are looking for an experienced Data Product Manager to lead the full life cycle of our data products. This is a high-visibility leadership role: these positions are historically hard to fill because they demand a genuine technical foundation in data, not just a product or analytics background, and the right professional will directly shape how our data initiatives are prioritized, delivered, and measured.
The Data Product Manager owns data products from ideation through deployment and optimization, combining technical depth, strategic thinking, and people leadership. This role operates at both the strategic level — defining roadmap and priorities with client and business stakeholders — and the operational level, staying close enough to the data architecture and delivery pipeline to make informed, credible decisions.
Responsibilities:
Data Lifecycle Management: Manage the complete data lifecycle, from data generation through pipelines to data enablement, ensuring each stage supports downstream analytics and consumption.
Data Architecture & Infrastructure: Understand the technical architecture and infrastructure that supports the organization's data needs, including storage, integrations, and analytics platforms, to make informed product decisions.
Task Prioritization & Roadmap: Collaborate with technical and business teams to understand data needs and priorities, and define the roadmap by balancing competing demands from different stakeholders based on business value.
Data Profiling: Analyze data types, relationships, patterns, and trends to build a clear understanding of the data landscape before defining requirements.
Requirements Definition: Partner with internal and external stakeholders to document data requirements that are clear, specific, and achievable, including how data should be presented for consumption.
Business Process Alignment: Understand business workflows in depth, enabling sound assumptions about sources, entities, and attributes when answering business questions.
Validation: Validate each product with users by testing it against real use cases and using data and metrics to confirm it meets their needs.
Performance Analysis: Monitor product performance through metrics and KPIs, using data-driven insights to drive continuous improvement of data initiatives and investments.
AI-Enabled Delivery: Support the incorporation of AI into the team's workflow to speed up delivery and decision-making.
Team Leadership: Lead cross-functional teams, including data scientists, data developers, and analytics specialists, to deliver high-quality data products. Attract, retain, and develop data talent by mentoring, training, and creating growth opportunities.
Requirements:
Advanced English proficiency (C1 or above), spoken and written, to communicate directly with international stakeholders
Solid, hands-on background in data and analytics environments — genuine technical depth is required, not only product or analytics-only experience
Experience managing data-related projects, including planning, execution, and stakeholder communication
Strong strategic thinking and product mindset, with experience in value-based prioritization and risk management
Proven experience leading and developing technical teams
Experience working within data platform environments hosted on Azure Cloud Services, including exposure to modern data transformation and warehousing tooling such as DBT and Snowflake
Experience using project management tools to plan, track, and communicate delivery status
Nice to Have:
Prior experience working with international clients across different time zones
Background transitioning from product management, project management, or technical team leadership (e.g., squad leadership) into data product roles
Experience with data governance practices
Experience with additional cloud platform providers (AWS or GCP)