Product Manager, Customer Data Platform
Rakuten Symphony (company site, opens in a new tab)7+ yrsOn-siteDirect career pageEst. 28–45 LPA
Posted on 25 Sept
Reach people at Rakuten Symphony
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Rakuten Symphony you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Own the end-to-end strategy, roadmap, and delivery lifecycle for Customer Data Platform and related data platforms.
- Act as the main technical liaison between business stakeholders, data scientists, and engineering teams to promote data-driven growth and adoption across Rakuten business units and external clients.
- Oversee the architecture of scalable data pipelines and curated datasets optimized for AI/ML initiatives, ensuring data governance and quality aligned to high-impact business use cases.
Minimum Requirements
- 7+ years of experience in Product Management and Data Engineering.
- Bachelor's degree in Technology (B.Tech) required; M.Tech/MS is optional.
- Technical proficiency with data modeling, warehousing, ETL/ELT pipeline design, and experience with SQL and at least one modern programming language (Python, Java, Scala, or NodeJS).
- Work Experience Required: 7+ years; Notice period: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Experienced in managing full Software Development Life Cycle (SDLC) for data platform products, indicating ability to lead complex projects end-to-end.
- Strong strategic collaborator comfortable bridging technical and business domains to translate complex requirements into actionable engineering plans.
- Domain expertise in data platforms with focus on scalable AI/ML data consumption, data governance, and customer-centric product delivery in a telecom or similarly data-driven environment.