Data Product Manager
C
CI&TData analytics
Brazil, Prior experience working with international clients across different time zonesFull-TimeManager
Salary not disclosed
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Job Details
- Languages
- Advanced English proficiency (C1 or above), spoken and written
- Required Skills
- AWSProject ManagementGCPSnowflakedbtData analytics
Requirements
- Have advanced English proficiency (C1 or above), spoken and written, to communicate directly with international stakeholders.
- Bring a solid, hands-on background in data and analytics environments with genuine technical depth.
- Have experience managing data-related projects, including planning, execution, and stakeholder communication.
- Demonstrate strategic thinking and a product mindset, including value-based prioritization and risk management.
- Have proven experience leading and developing technical teams.
- Have experience working in data platform environments hosted on Azure Cloud Services.
- Have exposure to modern data transformation and warehousing tools such as DBT and Snowflake.
- Have experience using project management tools to plan, track, and communicate delivery status.
- Prior experience with international clients across different time zones is a plus.
- Experience with data governance practices is a plus.
- Experience with AWS or GCP is a plus.
Responsibilities
- Manage the data lifecycle from data generation through pipelines to data enablement.
- Understand data architecture and infrastructure, including storage, integrations, and analytics platforms.
- Define product roadmaps and prioritize competing stakeholder needs based on business value.
- Analyze data types, relationships, patterns, and trends before defining requirements.
- Document clear, specific, achievable data requirements with internal and external stakeholders.
- Validate data products with users against real use cases and metrics.
- Monitor product performance through metrics and KPIs and use insights to improve data initiatives.
- Support incorporating AI into team workflows to speed delivery and decision-making.
- Lead cross-functional teams of data scientists, data developers, and analytics specialists; mentor and develop data talent.
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