Data Strategist
New
BrazilFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- AWSAgileDatabricks
Requirements
- 5+ years of experience in Data Product Management, Data Strategy, or Analytics roles in complex enterprise environments.
- Strong experience in financial services, such as banking, fintech, credit, insurance, or related sectors.
- Proven ability to translate business requirements into structured technical or machine-readable specifications.
- Experience with backlog prioritization frameworks such as RICE, WSJF, or equivalent methodologies.
- Familiarity with modern cloud data ecosystems, particularly AWS and Databricks, enabling informed product decisions.
- Strong stakeholder management skills, acting as a bridge between technical teams and business users.
- Ability to operate in ambiguous, fast-paced environments with a strong results-oriented mindset.
- Experience working in agile environments such as Scrum or Kanban.
- Strong communication, facilitation, and alignment skills across senior business and technical audiences.
Responsibilities
- Lead discovery sessions with business stakeholders (credit, commercial, and executive teams) to identify needs, pain points, and opportunities, translating them into actionable product and technical specifications.
- Define, prioritize, and maintain the data product backlog using value-driven frameworks, ensuring alignment with roadmap phases such as discovery, MVP, and scale.
- Produce structured, machine-readable specifications that can be consumed by AI agents and integrated into the data knowledge base.
- Oversee the full lifecycle of data products, from ideation to activation, ensuring alignment between business goals, data quality, and user experience.
- Define and track KPIs and OKRs focused on operational efficiency, predictive accuracy, and business impact of data initiatives.
- Design data consumer experiences for different personas, including commercial and credit teams, ensuring usability through dashboards and CRM integrations.
- Collaborate closely with data architects and engineering teams to ensure technical feasibility across platforms such as AWS and Databricks.
- Support change management and adoption initiatives to ensure data products replace manual processes and are embedded into business operations.
- Communicate progress, risks, and product decisions clearly to both internal leadership and client stakeholders.
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