DataOps Engineering Manager (m/f/d)

Description

The team builds and runs the data ingestion platform, which uses Azure Databricks, Azure Data Factory (ADF) and Apache Kafka for event streaming, supporting both batch and event-driven ingestion within Microsoft Azure.

The platform relies on CI/CD, automated framework testing, monitoring, logging, error handling and optimisation to keep pipelines robust, scalable and easy to maintain.

This role combines managing people, hands-on technical ownership and stakeholder work. You will lead a team of 5+ engineers and stay involved in building the solutions they deliver.

Responsibilities

• Lead, coach and develop a team of 5+ DataOps engineers through regular one-on-ones, mentoring, performance management and career planning, building a team that values accountability, technical quality and learning.
• Stay hands-on: design, build, test and tune ingestion frameworks and production pipelines on Azure Databricks, ADF and Kafka, write code, take part in code reviews and solve difficult engineering problems.
• Set the DataOps direction and engineering roadmap: define technical priorities, guide how the ingestion frameworks evolve, and bring CI/CD, automated testing, monitoring, logging and error handling into Data Engineering while balancing delivery with long-term scalability and reliability.
• Work closely with Data Architects, engineering leads, product teams and business stakeholders to turn requirements into scalable solutions, set priorities, manage expectations and report progress and risks.
• Help improve pipeline performance, reliability, observability and cost efficiency, set engineering standards, reduce technical debt, troubleshoot production issues and push the team to keep raising the quality of its work.

Requirements

• Proven experience managing and developing engineering teams of 5+ people, ideally in Data Engineering, DataOps or platform engineering. You mentor engineers, give useful feedback, manage performance and build a collaborative team.
• Extensive practical experience designing, building and maintaining data ingestion pipelines with Azure Databricks, Azure Data Factory (ADF) and Apache Kafka. You write production-ready code, build ingestion frameworks, troubleshoot complex pipelines and contribute to delivery.
• Strong knowledge of CI/CD, automated testing, monitoring, logging, error handling and performance optimisation.
• Experience working with Data Architects, engineering teams and business stakeholders to turn requirements into technical solutions. You can run complex initiatives on your own, handle competing priorities, make sound architecture decisions and explain technical trade-offs clearly.
• You are comfortable being both a people manager and an active engineer. You know when to step back and when to get stuck in, and you value knowledge sharing and building reliable solutions together.

Conditions

Working from home is possible where the role does not require office presence. The place of work can be arranged individually, including up to 20 days a year from anywhere in the EU.

Benefits

• Individual development support through internal and external training.
• 30 days of paid vacation per year, plus an extra day on Rosenmontag, and the option of up to 10 days of unpaid vacation after one year with the company.
• Urban Sports Club membership (M package) for access to a wide range of sports offers.
• Regular team events and scheduled celebrations of successes.
• Site-specific benefits tailored to individual needs, covering health, family time and skill development.