Engineering Manager (Data Direction)

Role overview

We are looking for an experienced engineering leader in Germany to steer the development of secure, dependable, and scalable data platforms. This position blends hands-on technical judgment in data and platform engineering with strong people management and delivery accountability. You will guide cross-functional teams building modern data capabilities that power analytics, AI, and machine learning work.

Working across engineering, product, and business functions, you will influence architecture choices, engineering standards, and the long-term direction of the platform. The role also plays an important part in an AI-led transformation while maintaining strong governance, security, compliance, and operational discipline. It is a chance to shape engineering culture, grow talented teams, and deliver critical systems in a fast-moving environment.

Responsibilities

• Lead, coach, and develop cross-functional data and platform engineering teams while encouraging ownership, collaboration, and career progression.
• Take responsibility for delivery, quality, and technical results across data platform initiatives, keeping them aligned with business goals.
• Work closely with Product, Analytics, Data Science, Machine Learning, and senior engineering leaders to define and execute a scalable platform roadmap.
• Improve engineering execution through better planning, estimation, CI/CD, testing, code review, and release practices.
• Participate in architecture decisions for modern data systems such as batch processing, streaming, lakehouse setups, and hybrid infrastructure.
• Maintain strong availability, scalability, performance, observability, and reliability in production pipelines and platform services.
• Build security, privacy, data governance, compliance, and lineage into platform design and development workflows.
• Spot and lower technical and data debt while keeping delivery moving forward.
• Assist with hiring, team expansion, and the continued improvement of engineering practices.
• Encourage continuous improvement through clear technical standards, strong communication, and customer-oriented engineering choices.

Requirements

• At least 5 years of professional experience in software engineering, data engineering, or a closely related technical discipline.
• Demonstrated experience leading engineering teams in an Engineering Manager, Team Lead, or similar role.
• Good grasp of data engineering, backend systems, and data architecture concepts, with enough depth to participate in technical decisions.
• Experience delivering complex, production-ready data platforms or systems in high-demand environments.
• Experience in regulated or high-reliability sectors such as financial services or FinTech is a strong advantage.
• Solid understanding of modern data platform practices, including data modelling, distributed processing, orchestration, warehousing, and lakehouse technologies.
• Practical experience with batch and streaming systems, infrastructure automation, deployment methods, and CI/CD workflows.
• Familiarity with data observability, including quality monitoring, metrics, logging, alerting, lineage, and performance tuning.
• Strong leadership, mentoring, communication, and stakeholder management skills.
• Nice-to-have experience with AI and machine learning platforms, low-latency or high-throughput systems, trading or market-data products, data governance and regulatory compliance, and scaling engineering organisations.

Perks and benefits

• Remote-first setup with flexibility across Europe.
• Chance to lead meaningful engineering work that shapes the future of data and AI capabilities.
• High ownership and autonomy over technical strategy, team growth, and platform evolution.
• Opportunity to collaborate with skilled engineers and cross-functional partners on complex technical problems.
• Build secure and scalable systems in a performance-driven, innovation-focused environment.
• Support for professional development through leadership responsibilities and challenging technical work.
• A culture centred on engineering excellence, ongoing improvement, and measurable impact.

Additional information

This role is published on behalf of a partner company, which handles the full application review and next steps. Applications are assessed through an AI-supported matching process designed to shortlist candidates against the role’s core requirements. The shortlist is then shared with the hiring company, which manages interviews, assessments, and the final hiring decision.

Data privacy notice

By applying, you agree that your personal data may be processed to assess your suitability for the role and shared with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws, including GDPR. You can request access, correction, deletion, or objection to the processing of your data at any time.

AI tools may be used to support parts of the recruitment workflow, including application review, resume analysis, response assessment, and inconsistency checks using available information. These tools support the recruitment team and do not replace human judgment; the final hiring decision is always made by people.