Engineering Manager

Years of Experience: 8+ years in software engineering, including 2+ years managing engineering teams, ideally in fast-paced product startups or high-scale tech enterprises.

Engineering Leadership: A track record of leading teams to ship reliable, high-scale backend/distributed systems, with strong judgement on hiring, delivery, and raising the technical bar.

Data Science & Analytical Strength: Strong grasp of data science and statistics — experimentation and causal inference, forecasting, and optimisation/ML concepts — with the analytical ability to interrogate models and metrics rather than take them at face value. This is a core requirement, not a nice-to-have.

Distributed Systems Depth: Solid computer-science fundamentals across distributed systems, concurrency, event-driven architectures, and the trade-offs of the CAP theorem.

Technical Toolkit: Comfortable reading and reasoning about production code and data (SQL and a backend language such as Go, Python, or Ruby), and about the pipelines that feed models and metrics.

Architectural Mindset: A knack for first-principles problem-solving and a strong record of balancing Non-Functional Requirements like reliability, latency, scaling, and cost.

Iterative Mindset: A bias towards shipping early and iterating; a belief in small, incremental changes over large, multi-quarter undertakings.

Leadership & Ambiguity: Proven ability to navigate ambiguity, set clear technical and organisational expectations, handle stakeholders, and thrive in a fast-paced environment.

Education: Bachelor's/Master's degree in Computer Science or an equivalent technical field.

Managers who came up as strong ICs in backend/distributed systems and stayed technical enough to lead from the front on hard problems.

Those with a background in logistics, ride-hailing, quick commerce, or marketplaces, who understand two-sided supply/demand dynamics and real-time dispatch.

Leaders who treat data science as a first-class part of the product — dispatch, matching, and pricing — and can bridge engineering and DS effectively.

High-agency individuals who drive consensus across conflicting technical perspectives and hold the line on operational rigour.