Engineering Manager - Data Platform

At AutoScout24, our Data Platform Engineering team builds and operates the AWS-based platform that enables teams across the company to work with data independently. Built around Data Mesh principles, it provides the infrastructure, self-service tooling, and governance that allow domain teams to own and manage their data products. 

 
As Engineering Manager, you'll lead the team responsible for developing and operating this platform. The role combines people leadership with strong technical involvement, from architecture and complex engineering problems to reliability, performance, and cost optimization. 
We're also making AI a native part of how our Data Engineering organization works and how people use our platform. This includes bringing AI directly into the daily workflows of Data Engineers and Analytics Engineers, as well as making the platform more intelligent, easier to use, and more accessible to business users. 
 

What you'll do

• Build a team that takes ownership, makes sound technical decisions, and delivers independently.
• Evolve our AWS-based data platform, making decisions around architecture, reliability, performance, security, and cost.
• Work alongside engineers on complex technical problems, including hands-on implementation when needed.
• Develop and improve self-service capabilities for data pipelines, dataset discovery, access management, and data quality monitoring.
• Strengthen our Data Mesh implementation, including domain ownership, data contracts, access controls, and federated governance.
• Improve data quality, lineage, and observability through automation and platform-level controls.
• Work closely with Product, Analytics Engineering, Data Governance, and business stakeholders to understand problems and develop solutions.
• Integrate AI into existing engineering tools and workflows across Data Engineering and Analytics Engineering, improving how teams develop pipelines, build data models, test changes, review code, and troubleshoot failures.
• Build AI capabilities directly into the data platform, helping users discover and understand datasets, work with data using natural language, investigate issues, and complete tasks that previously required technical knowledge or manual steps. 

What we're looking for 
 

• 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. You use these tools extensively in your own engineering work and understand how to use them effectively beyond basic code generation.
• Proven experience integrating AI into engineering workflows across the SDLC, ideally for Data Engineering or Analytics Engineering teams. You've implemented solutions that engineers actually use in their daily work and can explain how they improved efficiency.
• Experience building AI functionality into internal platforms or products, rather than just developing standalone chatbots. You understand how to integrate AI with existing tools, data, metadata, permissions, and workflows to make complex tasks easier for users.
• A product mindset, with the ability to understand business and user needs, challenge proposed solutions, and work effectively with Product and other stakeholders.
• Deep AWS expertise, particularly in designing, building, and operating production data platforms using services such as S3, Glue, Athena, IAM, MWAA and Lake Formation.
• Strong understanding of data lake and lakehouse architectures, including storage, processing, metadata, security, performance, and cost.
• 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.
• Experience implementing data quality, data contracts, observability, and access controls within production data platforms.
• Strong communication and people leadership skills, with the ability to develop engineers, delegate responsibility, and build an effective, independent team. 

A culture of growth  

With over 50 nationalities represented, we’re proud to welcome people of all backgrounds to our growing community, and we’re always finding new ways to help people feel welcomed and included. Here, you’ll have the tools, training and support you need to work in a way that suits you, learn new skills and reach your potential.  

For a career where you can drive our business and shape your future, apply now.