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About the Role
We are seeking a motivated ML Ops Data Engineer to support our data strategies. In your daily work, you will focus on developing data-driven applications and have the opportunity to participate in various projects. Our Data & Analytics team facilitates sustainable growth for our clients by easing their transition from intuitive to objective decision-making through reliable data collection, implementation of suitable data infrastructure, and effective data initiatives. We firmly believe that the 'decade of data' has begun: powerful technologies are ready to transform raw data into real insights, products, features, and more. We are looking for talented individuals from diverse backgrounds to join us on our journey to leverage data and achieve real impact through scalable ML/AI infrastructures, thorough analyses, and meaningful correlations, ensuring meaningful application.
Responsibilities
- Build high-quality data warehouses, cloud infrastructures, AI workflows, etc.
- Integrate data from various systems into flexible and consistent representations.
- Investigate and evaluate the long-term impact of AI use cases and their implementation.
- Ensure all employees and IT systems in the company have easy access to data through various frontends and interfaces.
- Work within an agile software development process in close cooperation with the Analytics, Product Development, and Software Development teams.
- Work in a great cross-functional team environment, thereby influencing the business.
Requirements
- Genuine interest in data and algorithms, and enthusiasm for solving difficult business problems with scalable data products.
- Knowledge of version control systems, web technologies, software, best practices in Analytics Engineering and Data Engineering, and the functioning of database systems.
- Solid experience with SQL, Python, and dbt.
- Experience with machine learning and/or AI is an advantage.
- Optional: The ability to translate data science into something that creates business value.
- Willingness to learn.
- Good communication skills in German and English (native or native-like level).
Skills
- SQL
- Python
- dbt
- Machine Learning
- AI
- Data Warehousing
- Cloud Infrastructure
- AI Workflows
- Data Integration
- Agile Software Development
- Analytics Engineering
- Data Engineering
- Database Systems
- Version Control Systems
- Web Technologies
Location
- Berlin
Work Type
- Full-time
Experience Level
- Mid-level
Education Level
- Computer Science Degree or equivalent qualification
Benefits
- Shape the future of innovation: Take the lead on groundbreaking projects across a variety of companies and regions.
- Work with an international team of digital natives: Unlock new opportunities for learning, co-creation, and thriving in a dynamic, multicultural environment.
- Career development: We support your growth in any direction—whether you want to deepen your expertise, lead a department, or explore new areas.
- Embrace change and new technologies: We actively try out new tools and AI capabilities to optimize our workflows and processes, giving you creative freedom and autonomy to achieve your goals.
- Exchange and discover: From team lunches to fun offsites and regular meetups, you will build lasting connections through regular events and dynamic knowledge-sharing opportunities.
About the Company
- A11 is the executive growth driver behind Europe's leading tech unicorns like Trade Republic, Sennder, and Kry.
- We are a SWAT team for business performance with expertise in Marketing, Sales, Data, Tech, and People Ops.
- With over 100 international experts, we tackle complex challenges in business and technology with precision.
- Whether it's product launches in record time or the transformation of entire business models – we deliver measurable impact.
Equal Opportunity
- A11 is committed to diversity and equal opportunity, applying equally to our employees and candidates.
- We value people – with all their wonderful, diverse backgrounds, perspectives, and experiences.
- Our diverse team has different ethnic and cultural backgrounds, gender identities, sexual orientations, family situations, religious and political affiliations, socioeconomic statuses, age groups, and abilities.