About this role
We’re looking for a data practitioner who is passionate about building reliable data foundations. You’ll be the person ensuring that our pipelines are robust, data is validated, and stakeholders can trust the insights and AI models that depend on it. More than just moving data, you’ll care deeply about data quality, business context, and technical excellence.

What you’ll do

• Design, build, and maintain ETL/ELT pipelines that are scalable, efficient, and easy to monitor.
• Implement data validation and quality checks, ensuring datasets are consistent, accurate, and production-ready.
• Collaborate with data scientists, ML engineers, PMs, and domain experts to understand data needs and translate them into solid pipelines.
• Debug issues in pipelines and proactively prevent future problems by improving observability and documentation.
• Balance business needs (delivering the right data fast) with technical excellence (ensuring long-term maintainability).

Who we’re looking for

• Technical stack: Strong SQL skills and hands-on experience with ETL/ELT tools and Python for data workflows. Comfortable with data warehouses/lakes and version control.
• Data quality mindset: You believe that “garbage in, garbage out” is real, and you are obsessed with validating and ensuring the trustworthiness of data.
• Business & product sense: You don’t just move data blindly — you care about why it matters. You seek to understand the business context behind the data and ensure your pipelines serve actual product and business needs.
• Builder & optimizer: You are persistent and curious, breaking down complex data problems into shippable steps, iterating quickly, and continuously improving systems.
• Technical excellence: You care about clean, maintainable, and well-documented code, and you follow best practices in testing, monitoring, and CI/CD for data.
• Communication & collaboration: You can clearly explain data issues and trade-offs to non-technical stakeholders. You work cross-functionally to align on requirements and deliver the right solution.
• Startup mindset: Comfortable with ambiguity and open-ended problems. Autonomous and proactive: when you see a broken pipeline or unclear requirement, you fix it or propose a better way.

Bonus points

• Experience with modern data stack tools (dbt, Airflow, Snowflake, BigQuery, Databricks, etc.).
• Background in data governance, observability, or data contracts.
• Knowledge of business domains (finance, manufacturing, pharma, retail, supply chain…) that helps bridge technical and business requirements.
• Experience supporting AI/ML pipelines with high-quality data inputs.

Founded 2020 in Munich, we are a rapidly expanding scale-up in the B2B SaaS area. We've already assembled a super innovative, smart and fun team of 320+ highly motivated employees around our offices in Munich, Barcelona, Madrid, Cluj and New York.   

At Aily Labs, we have the bold mission to democratize AI. Our groundbreaking product is an AI-powered mobile app that uses cutting edge GenAI traditional ML to unlock valuable business insights and gives personalized recommendations. Our aim? Disrupting the way corporate entities operate, paving the way for the world's first AI decision intelligence platform that enables faster, simpler and smarter decision-making across the entire value chain, aiming towards full Agentic automation of key business goals.