
Senior Product Manager – Parts Data at Partao (South Africa)
Partao· South Africa·
Role details
Work type
Remote
Employment
Full-Time
Job description
About the Role
We're looking for a Product Manager with a deep understanding of data architecture, a sharp technical mind, and a passion for leveraging AI to structure, standardize, and surface complex information. This role sits at the heart of our data platform and will shape how the heavy machinery-parts world connects. This is a fully remote role open to candidates globally. Strong English proficiency is essential, and the role pays approximately €1800 - €2400 per month depending on experience.
What You’ll Do
Define Data Models
- Design flexible, scalable data schemas to represent agricultural parts, equipment, and compatibility (fitment) relationships
- Work closely with data engineers to refine taxonomies and part hierarchies
- Ensure models support both human usability and AI-readability Drive Data Normalization Algorithms
- Design rule-based and ML-enhanced systems for cleaning and standardizing messy supplier and OEM data
- Prioritize approaches that improve matching accuracy and part deduplication
- Define KPIs and test frameworks to measure normalization effectiveness Leverage AI and Automation
- Partner with ML engineers to identify where AI can improve categorization, entity extraction, and compatibility inference
- Guide AI product strategy—from training dataset definition to UX for AI-powered features
- Stay current with generative and traditional AI techniques relevant to structured data Define Interfaces
- Specify APIs and internal tooling interfaces to power product search, part selection, and fitment validation workflows
- Collaborate with frontend and backend teams to ensure seamless integration and performance
- Champion developer experience and documentation standards
What You Bring
- 4+ years in product management, ideally in a data-heavy domain (e.g., eCommerce, B2B marketplaces, catalog platforms, or supply chain tech)
- Experience working on schema definition, data pipelines, or data platforms
- Proven ability to partner cross-functionally with engineers, data scientists, and operations teams
- Familiarity with data normalization, entity resolution, or catalog management problems
- Understanding of how to evaluate and integrate AI/ML systems into product workflows
- A builder’s mindset: willing to dive deep, write specs, draw schemas, and iterate quickly
- Excellent written communication and a high bar for clarity and detail
- University degree, ideally in a science, technical or business domain
Bonus Points
- Experience with agricultural equipment, industrial parts, or automotive catalogs
- Exposure to LLMs, embeddings, or vector search applied to structured data
- Prior work in remote-first or distributed teams
- Proficiency in at least one additional European language (e.g., German, French, Spanish, Italian, Polish)
Why Join Us?
- Shape the data backbone of a fast-scaling B2B platform
- Work with real-world data that matters to customers every day
- Join a small, sharp, and globally distributed team
- Own critical decisions and make an impact from Day 1
What We Offer
- Opportunity to be a thought leader with a wide span of control in a fast-growing startup with experienced mentors
- A challenging and rewarding environment where you can directly impact the future of the company and the industry
Why work at Partao
- Culture: “Ambition meets impact” – a team that values ownership, collaboration, and solving real‑world challenges for farmers and builders [partao.com/careers].
- Remote‑first approach: Many tech roles are fully remote; Luxembourg office supports a hybrid model [builtin.com].
- Fast‑growing startup: Opportunity to shape the company’s future as one of Europe’s fastest‑growing agri‑tech marketplaces.
- Diverse, distributed team: Employees from 7 countries and a flat structure with strong representation in technical departments (43% of staff).
- Early‑stage equity & impact: Joining at pre‑Seed means significant ownership potential and direct influence on product and culture.