You will manage analytics engineering projects with a focus on data modeling and quality assurance. Your role includes building scalable data pipelines, maintaining documentation, and supporting AI adoption throughout the organization.
Anforderungen
- •Master's degree in relevant field
- •First work experience with ML projects
- •Interest in AI applications and business impact
- •Proficient in Python and ML libraries
- •Good understanding of core ML concepts
- •Good SQL knowledge for data manipulation
- •Familiarity with computer vision techniques
- •Experience with NLP techniques
- •Experience with deep learning architectures
- •Familiarity with Kubernetes workflows
- •Experience with data-visualization tools
- •Strong interest in AI technologies
- •Excellent communication skills in English
Deine Aufgaben
- •Manage the full lifecycle of analytics engineering projects.
- •Build clean and well-documented data models for reporting.
- •Design and optimize SQL-based dbt models for analytics.
- •Monitor data pipelines and ensure high data quality.
- •Resolve data anomalies and validate metrics proactively.
- •Construct and maintain scalable ELT/ETL pipelines.
- •Utilize dbt, SQL, and Python for efficient data processes.
- •Document data models, metrics definitions, and business logic.
- •Promote best practices in data governance and naming conventions.
- •Enable access to clean, AI-ready data for company-wide use.
- •Contribute to AI tooling education and encourage exploration.
Deine Vorteile
Monthly MILES credits or Deutschlandticket
Subsidized Urban Sports Club membership
Access to 1,500+ discount providers
Flexibility to work remotely and in-office
Attractive pension plan
Personal development opportunities
Support for regional social projects
Original Beschreibung
## Analytics Engineer
###### Permanent employee, Full-time ·Berlin
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##### Join the ride!
As a Analytics Engineer at MILES you will be responsible for building and maintaining the foundational data infrastructure that powers analytics across the organization. You will work at the intersection of data engineering and data analysis, transforming raw data into clean, well-modeled datasets that are trusted, easy to use, and optimized for business decision-making. Partnering closely with cross-functional stakeholders, you will own the development and maintenance of scalable data models, support data governance initiatives, and ensure data quality throughout the pipeline. Your work will be key to enabling data self-service, supporting advanced analytics, and fostering a culture of data-driven thinking across teams.
##### Your Responsibility
* End-to-End Ownership of Data Modeling & Pipelines: Own and manage the full lifecycle of analytics engineering projects, from data ingestion and transformation to production-ready, scalable data models. You will ensure alignment with analytics use cases by building clean, well-documented models that serve as the foundation for reporting.
* Data Transformation & Quality Assurance: Design, implement, and optimize SQL-based dbt models to support analytics across the organization. Ensure high standards of data quality by proactively monitoring pipelines, validating metrics, and resolving anomalies. Contribute to a culture of data reliability through automated tests, CI/CD practices, and clearly documented KPIs.
* Scalable & Maintainable Data Infrastructure: Build and maintain robust ELT/ETL pipelines that scale with data volume and complexity. Use a combination of dbt, SQL, and Python-based tools to create efficient pipelines. Continuously improve performance and maintain production stability through monitoring and observability.
* Documentation & Data Governance: Ensure data models, metrics definitions, and business logic are well-documented and version-controlled. Support data governance by promoting best practices in naming conventions, lineage tracking, and semantic consistency.
* AI & Tooling Enablement: Support company-wide adoption of AI and automation by enabling access to clean, AI-ready data. Enjoy the freedom to experiment, explore and build small applications of AI and RAG. Contribute to internal initiatives that educate teams on AI tooling.
##### Your Experience
* Education: You hold a Master’s degree in a relevant field such as Data Science, Computer Science, Engineering, Statistics or a related discipline.
* Experience: You have already gained first work experience as an intern, working student or full-time and had direct contact with real-world ML projects and applications.
* Profile: You want to make an impact by not just building models but also creating solutions that last. You're energized by turning raw data into valuable products, and you're not afraid to explore, test, fail, and improve. You have a general interest in Artificial Intelligence applications and their strategic impact on business decisions within the mobility sector.
* Technical skills:
* Proficient in Python and relevant ML libraries: scikit-learn, TensorFlow, Keras.
* Good Understanding of core ML concepts: supervised/unsupervised learning, evaluation metrics, cross-validation
* Good SQL knowledge for data extraction and manipulation
* Familiarity with computer vision and image analysis
* Nice to have:
* Experience with NLP techniques
* Experience with deep learning architectures (CNNs, transformers)
* Familiarity with Kubernetes and container-based deployment workflows
* Experience with data-visualisation tools to showcase the result of ML applications.
* AI Exposure: Strong interest in AI technologies and their practical application in business processes. Previous experience with AI tools is a plus.
* Languages: Excellent communication skills in English (both written and verbal). Proficiency in German is a significant advantage.
##### Benefits
* **Mobility:** Choose between monthly MILES credits or the Deutschlandticket.
* **Fitness:** Enjoy a subsidized Urban Sports Club membership for your physical and mental well-being.
* **Discounts:** Access 1,500+ providers for discounts on sneakers, theater visits, and more.
* **Home Office:** Enjoy the flexibility of working from our office in Berlin and from home.
* **Retirement:** Secure your financial future with our attractive pension plan.
* **Growth:** We prioritize personal development through knowledge sharing and training opportunities (with the support from our HR Team and the Team Leads).
* **Social Impact:** We dedicate a portion of our revenue to support regional social projects, actively contributing to the well-being of society and the environment. #milescharity