Analytics Engineer (f/m/x/d)

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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.

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.

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 Engineering, Data Science, Computer Science, Business Informatics, or a related discipline.
• Experience: 2-3 years of relevant experience in Data Engineering, Analytics Engineering or a related field. Ideally in a fast-paced environment such as a Start-Up or Scale-Up.
• Profile: You are detail-oriented and deeply analytical, with a strong drive to create robust and scalable data systems. You thrive on optimizing workflows, automating repetitive tasks, and building high-quality data pipelines that support downstream analytics. You take ownership, write clean and modular code, and care deeply about data quality, maintainability, and documentation.
• Technical Skills:

• Advanced SQL skills (preferred Snowflake). Comfortable writing, maintaining and improving complex queries, joins, aggregations, and data transformations.
• You have a good understanding of dimensional modeling and star/snowflake schema design. Experience building semantic layers (dbt Metric Layer) is a plus.
• Proficiency with Python, Airflow and dbt, with the ability to optimize materialization strategies for cost and performance.
• Familiarity with Git-based workflows
• While not your primary focus, experience with a data visualisation tool such as Tableau is a plus.

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

About Us
OUR VALUES
Our MILES values are the basis of our daily work and what makes us a team. They define how we treat each other at MILES and how we strive to bring the best of ourselves to our customers.
Here is a brief insight into what you can expect from us in your day-to-day:
Passion: Be yourself, have fun, and enjoy what you do.
Ownership: Strive for excellence and surprise yourself.
Resourceful: Be pragmatic. Use what we have first.
Curiosity: Feel free to challenge the status quo and be willing to adapt.
Support: Support each other and proactively ask for help.
Empathy: Always consider the position others are in.
About Miles
We are the leading car sharing provider in Germany and also offer long-term car subscriptions. Thanks to our cooperation and charity activities, part of our turnover goes towards regional and social projects.
At MILES, we believe in a world in which mobility is shared, sustainable, and accessible to all. With our offer, we create an alternative to private car ownership, reduce the number of vehicles on the roads, and positively contribute to urban life.
Become part of our diverse team, bringing talented people from over 50 countries together, each with their own experiences and ideas.
GOOD TO KNOW
Don\’t have a MILES account yet? With the code JOINUS15, you will receive €15 starting credit when you register for the first time. Enjoy the ride!

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology

• Industries

  Software Development

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