House Engineering Manager - Data Foundations New Remote Sweden

Remote Sweden

Our House Engineering Manager will be an integral part of our Engineering Leadership team in EMEA. This role is based remotely in the UK, Ireland, Sweden, Estonia or Israel.

DoiT is a global technology company that works with cloud‑driven organizations to leverage the cloud to drive business growth and innovation. We combine data, technology, and human expertise to ensure our customers operate in a well‑architected and scalable state – from planning to production. Delivering DoiT Cloud Intelligence, the only solution that integrates advanced technology with human intelligence, we help our customers solve complex multicloud problems and drive efficiency. With decades of multicloud experience, we have specializations in Kubernetes, GenAI, CloudOps, and more. An award‑winning strategic partner of AWS, Google Cloud, and Microsoft Azure, we work alongside more than 4,000 customers worldwide.

The House Engineering Manager is a hands‑on leadership role centered on enablement and delivery. Your primary responsibility is to ensure the House consistently delivers on its commitments by unblocking engineers, maintaining focus, and creating an environment where the team can perform at its highest potential. This is a technical role: you are expected to review engineering work, provide clear technical direction, and contribute to the codebase when needed. The balance between technical contribution and leadership depends on the team’s context, but your overarching mandate is to enable the team and own the execution and delivery of the House by having an in‑depth understanding and to be able to in‑practice be hands‑on on the team domain.

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• Leading a team of 5 to 10 engineers
  
• Driving ceremonies and the day‑to‑day operations of the team
  
• Be the enabler of the team, ensuring members are unblocked quickly and are clear about what they need to deliver and the value it will bring to users
  
• Responsible for the professional well‑being and career development of team members
  
• Manage team performance, provide continuous feedback and mentoring
  
• Help ensure high‑quality production releases by supporting the engineering release process, monitoring deployments, and upholding Production branch standards
  
• Review pull requests thoroughly and provide clear, actionable, constructive feedback
  
• Lead and collaborate on technical design discussions, ensuring architecture alignment; oversee high‑level technical activities and dive deep when needed
  
• Drive and own the technical roadmap, assess technical debt and ensure components scale and stay healthy
  
• Maintain an AI‑Driven mindset and evolve the team around AI‑driven development
  
• Work closely with the Technical Product Owner and UI/UX Designer to define, plan, and structure each sprint, ensuring priorities are well understood
  
• Plan for incoming business needs and maintain a house‑level roadmap aligned with product
  
• Balance sprint commitments with customer‑facing responsibilities by resolving support tickets, setting clear expectations, and prioritizing effectively.
  
• Follow an AI‑Driven software development lifecycle: human‑driven design, assuring quality while AI executes implementation
  

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• Upward: Communicate clearly and succinctly, giving leadership the right level of context and prioritising escalations appropriately.
  
• Downward: Empower senior engineers to own key areas and coach team members to stay focused and aware of their impact.
  
• Sideways: Collaborate effectively with other Houses, raising challenges and opportunities to support cross‑team alignment and stability.
  

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• Proven experience leading an engineering team (typically 5+ engineers) in a delivery‑focused environment (3+ years)
  
• Past experience as a software engineer for at least 5+ years
  
• Strong hands‑on technical background with ability to review code, guide design decisions, and dive deep when needed
  
• Experience owning delivery and execution: sprint planning, backlog management, release readiness
  
• AI‑Driven mindset, defaulting to AI while ensuring quality and consistency
  
• Demonstrated ability to mentor, coach, and grow engineers via regular feedback and performance management
  
• Strong communication skills, translating business context into clear technical direction
  
• Experience working in a SaaS, cloud‑native, or distributed systems environment
  

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• Strong hands‑on experience with Golang and Node.js (backend services, APIs, real‑time systems)
  
• Strong hands‑on experience with React (complex state management, performance optimisation, large‑scale front‑end applications)
  
• Strong hands‑on experience building Data Pipelines in an orchestrated manner using technologies such as Dagster or Airflow (or others)
  
• Solid experience designing and operating systems in cloud environments (AWS, GCP, Azure)
  
• Strong understanding of cloud fundamentals: managed pipeline orchestration, compute, API analysis for data extraction and transformation
  
• Familiarity with Infrastructure as Code tools such as Terraform or similar
  
• Understanding of distributed systems concepts: consistency, availability, observability, fault tolerance
  
• Strong knowledge of system reliability, performance tuning, and production incident management
  

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• Experience in cloud‑native applications
  
• Hands‑on experience with more than a single cloud provider
  
• Background in scaling teams, processes, or technical systems as the organisation grows
  

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• Unlimited vacation
  
• Flexible working options
  
• Health insurance
  
• Employee stock option plan
  
• Professional development stipend
  

DoiT unites as Many Do’ers, One Team, where diversity is more than a goal—it’s our strength. We actively cultivate an inclusive, equitable workplace, recognising that each unique perspective enhances our innovation. By celebrating differences, we create an environment where every individual feels valued, contributing to our collective success.

At DoiT International, we are committed to cultivating a diverse and inclusive workplace and collecting gender data for diversity and inclusion programmes. This information is segregated from employment records and handled in an aggregate, de‑identified manner to protect anonymity. xcfaprz