Engineering Manager - Data Platform (AI)

Location: Berlin, Germany

Company

hirify.global operates an AWS-based data platform that enables teams to independently manage data products through Data Mesh principles, self-service tooling, and governance.

What you will do

• Build, hire, coach, and develop an engineering team that takes ownership and delivers independently.
• Evolve the AWS-based data platform across architecture, reliability, performance, security, and cost optimization.
• Work hands-on with engineers to solve complex technical problems and improve production platform reliability and efficiency.
• Develop self-service capabilities for data pipelines, dataset discovery, access management, data quality monitoring, lineage, and observability.
• Strengthen Data Mesh implementation through domain ownership, data contracts, access controls, and federated governance.
• Integrate AI into Data Engineering and Analytics Engineering workflows and platform capabilities, including data discovery, natural-language data interaction, troubleshooting, code review, testing, and failure investigation.

Requirements

• 5+ years of experience as an Engineering Manager, including hiring, coaching, and developing engineering teams.
• Strong software or data engineering background, 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, including use beyond basic code generation.
• Experience integrating AI into engineering workflows across the SDLC, ideally for Data Engineering or Analytics Engineering teams, with solutions used in daily engineering work.
• Experience building AI functionality into internal platforms or products, integrating AI with tools, data, metadata, permissions, and workflows rather than only developing standalone chatbots.
• Product mindset and ability to understand business and user needs, challenge proposed solutions, and collaborate with Product and other stakeholders.
• Deep AWS expertise in production data platforms, particularly 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, 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 in production data platforms.
• Strong communication and people leadership skills, including developing engineers, delegating responsibility, and building an effective independent team.

Culture & Benefits

• Inclusive community representing more than 50 nationalities.
• Tools, training, and support for professional development and learning new skills.
• Work environment designed to support individual working styles and long-term growth.