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

At AutoScout24, the 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 will 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. The Data Engineering organization is also making AI a native part of how it works and how people use the platform.

Responsibilities

Build a team that takes ownership, makes sound technical decisions, and delivers independently; Evolve the 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 the 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; 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

Requirements

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, ideally for Data Engineering or Analytics Engineering teams; Experience building AI functionality into internal platforms or products, rather than just developing standalone chatbots; 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

Benefits

Tools, training and support to work in a way that suits you; Opportunities to learn new skills and reach your potential; Culture of growth in a diverse, inclusive community