# Manager, Software Engineer at Delivery Hero (talabat)

Delivery Hero (talabat) is hiring a Manager, Software Engineer in Barcelona, Spain. Level rates it Works on AI ●●●○; you can [apply on Delivery Hero (talabat)](https://jobsbylevel.com/go/4b86515b-f85f-4e7c-a902-6692fed268a0?utm_medium=ai-agent).

AI Level 3, AI centrality 70 out of 100. Barcelona, Spain.

## Details

- Company: [Delivery Hero (talabat)](https://jobsbylevel.com/companies/delivery-hero-talabat)
- AI level: AI Level 3 (score 70 out of 100)
- Location: Barcelona, Spain
- Posted: October 28, 2026
- Apply: https://jobsbylevel.com/go/4b86515b-f85f-4e7c-a902-6692fed268a0?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=manager-software-engineer-at-delivery-hero-talabat-0e3e86

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## Description

Glovo is part of the Delivery Hero Group, the world’s pioneering local delivery platform, our mission is to deliver an amazing experience—fast, easy, and to your door. We operate in around 65 countries worldwide. Headquartered in Berlin, Germany. Delivery Hero has been listed on the Frankfurt Stock Exchange since 2017 and is part of the MDAX stock market index. The Budget Steering squad builds a holistic approach to budget allocation and optimization for performance marketing — from quarterly planning to monthly optimization down to daily decisions at campaign and ad-group level. We operate in a highly complex and ambiguous environment where: Ground truth is often unobservable (incrementality vs attribution) Budget decisions must be made continuously, under uncertainty and with imperfect data Every allocation change moves real spend across markets, channels and platforms Our goal is simple to state and hard to solve: invest each euro where it generates the biggest leverage , across scenarios ranging from volume maximization to payback-based allocation. We are looking for an Engineering Manager to lead a cross-functional squad of engineers and data scientists , own a large-scale production service the business depends on daily, and turn ambiguous commercial questions into reliable, model-driven decision products . This role requires a strong technical foundation — in backend engineering or in data science / ML — combined with the leadership to grow people and the pragmatism to partner closely with Product and business stakeholders. In this role you will, Lead and grow a cross-functional squad Lead engineers and data scientists across the full product lifecycle — from problem framing to production and adoption Grow individuals through coaching, feedback and clear development paths, and hire to close capability gaps Set measurable goals for the team and create the conditions for the squad to hit them Build a culture of ownership, proactiveness and high engineering standards Own the budgeting lifecycle end to end Take accountability for budget allocation across every dimension and timeline — from strategic quarterly allocation to daily bid and budget changes at campaign level Drive the development of payback-based allocation models , including CLV estimation and constrained optimization Consolidate a fragmented tool stack into a single budgeting platform with coherent interfaces, ownership and roadmap Balance methodological rigor with business constraints — budget caps, pacing and channel dependencies Guide technical strategy and execution Shape the squad's technical strategy and stay close enough to the work to be a credible partner in most technical conversations at squad and domain level Make architecture and prioritization trade-offs explicit — effort, value, feasibility and pace Set the bar for reliability and data quality : uptime, correctness of allocation, and validated inputs and outputs across every source Ensure solutions are built as decision products , not one-off analyses — tested, monitored, documented and reproducible Partner with Product and business stakeholders Work with Product Managers to define scope, trade-offs and timelines, and to set common, measurable goals across planning cycles Act as an ally of Product: negotiate constructively, know when and how to say no, and compromise without losing the long-term technical direction Reduce ambiguity by asking the right questions before committing the team to build Navigate a complex stakeholder network spanning marketing, finance, analytics and central platform teams Drive decision-making under uncertainty Provide clear recommendations despite imperfect measurement , articulating trade-offs and confidence levels Navigate conflicting signals (e.g., attribution vs incrementality vs MMM) and help the team decide what to trust Translate complex modeling and system behaviour into clear narratives for non-technical audiences Build trust in the squad's outputs over

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