Head of Data Engineering

Role overview

This is a senior data leadership opportunity based in Germany and handled by a partner employer. The role sits in a fast-moving technology environment where you will shape a global data ecosystem, set technical direction, and drive the systems that support analytics, reporting, and machine learning.

As the Head of Data Engineering, you will combine strategic thinking with hands-on technical execution. Your focus will be on building resilient, scalable data platforms, improving reliability, and guiding engineering practices that support business growth across international teams.

You will also have the freedom to influence technology choices and help define best practices in a remote-first setup.

Key accountabilities

• Own the direction, design, and delivery of a scalable data landscape that can keep pace with global expansion.
• Set engineering standards for data pipelines, including CI/CD, automation, source control, and strong operational discipline.
• Strengthen data security, governance, performance, and reliability across systems used for analytics and machine learning.
• Make key technical choices around cloud platforms, tooling, and data engineering approaches.
• Lead, coach, and develop data engineering talent while encouraging accountability, collaboration, and continuous learning.
• Oversee the creation of efficient ETL/ELT workflows and modern data processing patterns.
• Work closely with business, product, analytics, and technical partners to turn complex needs into scalable solutions.
• Build processes that improve data quality, accessibility, and the overall effectiveness of the data function.

Requirements

• Strong background leading data engineering in a fast-growing, scale-up, or technology-led environment.
• At least 3 years of experience managing and developing engineering teams, with the ability to mentor technical professionals effectively.
• 5+ years of practical experience using languages such as Python, Java, or Scala to build data systems.
• Solid understanding of data architecture, data warehousing, big data technologies, and cloud infrastructure.
• Proven experience working with relational databases and NoSQL systems at scale.
• Hands-on expertise with Google Cloud Platform and cloud-native data solutions.
• Ability to design data pipelines that are secure, dependable, and high performing.
• Strong technical leadership with a clear focus on engineering quality and ownership.
• Excellent communication and teamwork skills, with the ability to work across multiple functions.
• An advanced degree in Computer Science, Engineering, or a related discipline is beneficial.

Benefits

• Remote-first working model with the freedom to work from anywhere in the world.
• Chance to influence the technical strategy and data foundation of a global technology business.
• A culture that supports sustainable performance and healthy work-life balance.
• High-impact leadership position with ownership of essential data systems and engineering practices.
• Exposure to international teams and products used across global markets.

Application and process details

This opportunity is posted on behalf of a partner company, which handles applications and the next stages of the hiring process. A matching system is used to review applications quickly and fairly against the role’s core requirements. The shortlist is then shared with the hiring company, while interviews and assessments are managed internally by that employer.

Data privacy and AI screening notice

By applying, you consent to your personal information being processed to assess your suitability and share relevant details with the hiring employer. This is done under legitimate interest and pre-contractual steps, including under GDPR where applicable. You may request access, correction, deletion, or objection at any time.

Artificial intelligence tools may be used to support parts of the recruitment process, such as resume review, application analysis, response evaluation, and detecting possible inconsistencies or verification signals. These tools assist the recruitment team but do not replace human judgment. Final hiring decisions are made by people.