Data Product Manager
New
C
CI&TData analytics
ColombiaFull-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, with experience in value-based prioritization and risk management.
- Have proven experience leading and developing technical teams.
- Have experience working within 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 complete data lifecycle, from data generation through pipelines to data enablement.
- Understand the data architecture and infrastructure, including storage, integrations, and analytics platforms.
- Collaborate with technical and business teams to define the roadmap and prioritize competing demands based on business value.
- Analyze data types, relationships, patterns, and trends to understand the data landscape.
- Partner with stakeholders to document clear, specific, achievable data requirements.
- Understand business workflows to make informed assumptions about data sources, entities, and attributes.
- Validate products with users against real use cases and confirm they meet user needs using data and metrics.
- Monitor product performance through metrics and KPIs and use insights to improve data initiatives and investments.
- Support incorporating AI into the team's workflow to speed delivery and decision-making.
- Lead cross-functional data teams and mentor, train, and develop data talent.
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