Senior Data Engineer

Quick Facts

• Role: Senior Data Engineer
• Focus: Build and operate a Databricks-based data engineering & analytics platform
• Domain: Cloud-native ETL/ELT (batch + streaming), data quality, governance, and DevOps/MLOps operationalization

Description

You will be responsible for the operation and continued development of the company’s data engineering and analytics platform built on Databricks. Working with Data Scientists, data architects, and business teams, you will build data pipelines and curated datasets to enable data-driven decisions and AI applications, integrating and transforming data from multiple source systems.

You will ensure data quality through automated validations, monitoring, alerts, and clear governance rules, and operationalize analytics, ML, and AI pipelines using DevOps/MLOps principles with CI/CD, reproducible deployments, and reliable production operations.

Responsibilities

• Operate and enhance the Data Engineering & Analytics platform based on Databricks
• Develop data pipelines and curated datasets with Data Scientists, data architects, and business stakeholders
• Integrate and transform data from diverse source systems for advanced analytics, machine learning, and AI
• Guarantee data quality via automated validations, monitoring, alerts, and governance rules
• Operationalize analytics/ML/AI pipelines using DevOps/MLOps practices (CI/CD, reproducible deployments) and ensure reliable operations
• Contribute to evolving data engineering principles and standards; drive new technologies and best practices

Requirements

• Multi-year experience as a Data Engineer building and operating cloud-native ETL/ELT pipelines (batch and streaming)
• Degree in natural sciences/engineering, mathematics, (business) informatics, or a related field with relevant focus
• Hands-on experience with Databricks
• Cloud expertise (Microsoft Azure and/or AWS)
• Good knowledge of Python and SQL plus strong methodological software engineering understanding
• Experience with orchestration, CI/CD, Infrastructure as Code (e.g., Terraform), and containerization
• Strong understanding of data modeling, lakehouse principles, and governance as a foundation for scalable data and AI infrastructure
• Willingness to lead projects
• Team orientation, strong communication, initiative, high quality awareness, and motivation to learn business processes

Benefits

• 37.5-hour work week and campus environment with structured onboarding and regular feedback
• Personal development opportunities and regular feedback meetings
• Childcare on campus (Kita)
• Holiday and Christmas bonuses, BAV, VL
• Corporate benefits, employee discount, and bike leasing
• 30 vacation days and a free fitness studio
• Modern workplaces with campus garden and coffee hubs/food spots, plus internal events