Product Manager - Order Fulfilment

About the role

Mr D, a division of takealot.com, is looking for a Product Manager (order fulfilment) to join its team in Cape Town. The role owns the roadmap and execution of the order fulfilment product portfolio, covering the customer journey from restaurant order acceptance through delivery, including order tracking, delivery timelines, late and delayed orders, restaurant handovers, driver assignments and delivery updates. It reports to the Product Lead (Order fulfilment).

Key responsibilities

• Manage the execution and rollout of order fulfilment features, from design, documentation, implementation, testing and launch to success metric monitoring.
• Write detailed product specifications for engineering and design teams, using traditional and AI-accelerated methods for mobile apps, back-end logic, APIs, integrations and internal tools.
• Collaborate with engineering, UX, QA and other teams: define objectives, epics, user stories and acceptance criteria, run UAT, and help with technical design decisions.
• Work with the drivers, restaurant partners, groceries, logistics, customer support and operations teams.
• Define and report on success metrics such as on-time delivery rate, order accuracy, average delivery time and late/delayed order rates, and move the team's North Star metric forward.
• Analyse quantitative and qualitative data to find opportunities for fulfilment optimisation.
• Own the product roadmap and backlog, prioritising with the Head of Product, Product Lead and stakeholders.
• Validate customer solutions with UX, sign off on designs (including copy) and manage stakeholder relationships and integrations with Takealot Fulfilment Services.

Required profile

• At least 3 years as a Product Manager, or 5 years in a software development related role (e.g. Business Analysis, Product Owner).
• Bachelor's degree or Advanced Diploma in a related field; equivalent experience accepted otherwise.
• Experience with data-driven product decisions, wireframing and design solutions.
• Strong technical acumen for integration, and knowledge of machine learning, LLM and AI concepts.

Required skills

• Writing specifications by traditional and AI-accelerated methods.
• Data analysis and decision-making.
• Wireframing and design solutions.
• ReactJS, Python, Scala, Kotlin, Swift, Google Cloud, Kafka, Redis, Kubernetes and machine learning (listed as part of the tech stack).

What we offer

• Total remuneration package with flexible pay options.
• Hybrid working model.
• Mentorship programme and access to online learning courses.
• Regular social events, staff discount and birthday leave.
• Confidential counselling, legal support and financial guidance.
• Mac or Windows computers, two monitors, and free parking.