Engineering Manager - Data Platform (m/f/d)

AutoScout24, a major player in the online automotive marketplace, is seeking an experienced Engineering Manager to lead their Data Platform team. This role is a unique blend of high-level people management and deep technical architecture, focused on scaling a platform built on Data Mesh principles. If you are an experienced leader who enjoys staying hands-on with emerging AI trends and cloud infrastructure, this remote opportunity offers a chance to drive data democratization at a massive scale.

About the role

The Data Platform team at AutoScout24 acts as a bridge between complex infrastructure and domain-specific data needs. By leveraging AWS, the team provides the self-service tooling, governance, and reliability required for other departments to manage their own data products independently. As the Engineering Manager, you will not only be responsible for the health and growth of the team but also for shaping the technical roadmap.

A significant focus of this role is the integration of AI into the platform. You will lead initiatives to embed AI-driven workflows into the daily lives of Data and Analytics engineers. This includes enhancing the platform with intelligence that simplifies dataset discovery, automating quality monitoring, and enabling business users to interact with data using natural language, effectively lowering the barrier to entry for non-technical stakeholders.

What you’ll do

• **Team Leadership:** Cultivate a high-performing engineering culture centered on ownership, accountability, and technical excellence. You will be responsible for hiring, coaching, and mentoring a team of skilled data engineers.
• **Architectural Strategy:** Lead the evolution of the AWS-based data platform. You will be expected to make critical decisions regarding system performance, security, cost optimisation, and architectural scalability.
• **AI Integration:** Drive the adoption of AI-assisted engineering. This involves integrating tools like Cursor or Codex into the software development lifecycle and building AI functionality directly into the platform to automate data lineage and troubleshooting.
• **Stakeholder Engagement:** Act as a central point of contact for Product, Data Governance, and Analytics teams. You will translate complex business problems into actionable technical solutions while fostering a federated governance model.
• **Hands-on Technical Contribution:** Even in a management capacity, you will need to remain close to the code, participating in architecture reviews and assisting with complex engineering challenges when necessary.

What they’re looking for

To succeed in this role, you will need a robust background in both engineering management and data platform architecture:

• **Management Experience:** At least 5 years of experience leading, coaching, and developing engineering teams with a proven track record of delivery.
• **Technical Proficiency:** Deep expertise in AWS, data lake/lakehouse architectures, and a strong command of Python and SQL. Familiarity with infrastructure-as-code and CI/CD pipelines is essential.
• **AI Specialisation:** Demonstrable experience integrating AI development tools into engineering workflows and building AI-enabled features into internal data products.
• **Data Mesh Principles:** A solid understanding of decentralised data ownership and federated governance.
• **Strategic Mindset:** A product-focused approach, ensuring that the platform meets the evolving needs of the business while remaining reliable and user-friendly.

For a South African candidate, this remote role is an excellent opportunity to work with a high-scale European platform. Roles of this nature, particularly those combining advanced data engineering with AI leadership, typically command high market-related packages in the tech sector. Career progression for an individual in this position usually leads toward roles like Head of Data, Director of Engineering, or Chief Technology Officer, especially in organisations that are scaling their digital and AI capabilities.

• 5+ years of experience as an Engineering Manager, with a strong track record of hiring, coaching, and developing engineering teams.
• Strong software or data engineering background, with recent hands-on technical experience and the ability to contribute to complex engineering decisions.
• Extensive hands-on experience with AI development tools such as Claude Code, Codex, Cursor, or similar.
• Proven experience integrating AI into engineering workflows across the SDLC.
• Experience building AI functionality into internal platforms or products.
• A product mindset, with the ability to understand business and user needs.
• Deep AWS expertise, particularly in designing, building, and operating production data platforms.
• Strong understanding of data lake and lakehouse architectures.
• Experience operating large-scale data platforms, troubleshooting production issues, and improving reliability and efficiency.
• Proficiency in Python and SQL, along with practical experience in infrastructure as code, CI/CD, testing, and software engineering best practices.
• Practical experience with Data Mesh principles, decentralized data ownership, self-service data infrastructure, and federated governance.
• Strong communication and people leadership skills.