About dlthub
At dltHub, we're building on the success of dlt, the most popular open-source library for data loading in Python with ~ 4 million monthly downloads.
After proving its value in the OSS community, we’re now building dltHub to make data engineering accessible to all Python developers, whether they’re launching their first analytics workflow or powering full ML-driven organizations.
Our mission is to make data engineering as accessible, collaborative, and frictionless as writing Python itself. dltHub is a workspace and runtime that empowers any Python developer to build, run, and maintain data pipelines, transformations, and notebooks, without needing a data platform or infrastructure team.
Our team is based in Berlin, now growing into other locations, especially across the US. Founded by experienced data and ML engineers, we're backed by Foundation Capital, Dig Ventures, and technical founders from Hugging Face, Instana, Matillion, Miro, MotherDuck, Datadog, Mode, and Rasa.
Our team is driven by clear values: we speak with courage, build what matters, automate relentlessly, show up with energy, deliver on commitments, and win together.
🚀 About the Role
We are building the next generation of AI-native data tooling - building our AI-first data platform on top of our popular open-source data ingestion core.
We are looking for an entrepreneurial software engineer based in Berlin who thrives in a fast-paced environment with a high degree of autonomy and ownership. You will work on solving data platform challenges for our customers: ingestion, storage, performance, reliability, observability and AI-assisted developer experience. If you enjoy working with an ambitious and driven team and care deeply about code quality, data systems, and building tools that engineers enjoy using, this role is for you.
🗂️ Key Responsibilities
- Own features end-to-end: design, planning, implementation, tests, documentation, maintenance and improvements.
- Shape architecture and technical direction through code and design discussions.
- Contribute to a culture of engineering excellence by maintaining high standards for code quality, observability, scalability and security.
- Work with our solution engineering team and customers to turn user problems into clean, maintainable solutions.
- Design and implement solutions that integrate with modern data stacks: warehouses, lakes, object storage, and analytics engines.
- Mentor teammates and Open Source contributors, raising the bar for engineering quality.
- Contribute to our Open-Source Core by building features and engaging with the community e.g. via PR reviews or collaboration.
- Sustain a culture of experimentation by keeping up with developments in the Python ecosystem, AI-assisted development workflows, and evolving data architectures and technologies.
Requirements
What We’re Looking For
✅ Qualifications
- 7+ years of experience in software development and/or data engineering.
- Experience in designing scalable systems.
- Strong Python skills: clean design, typing, testing, and maintainable code.
- Solid understanding of data engineering fundamentals: data ware-/lakehouses, object storage, data ingestion and transformation patterns.
- Good SQL knowledge and understanding of databases, transactions, and concurrency.
- Experience working with modern Python data tools (e.g. DuckDB, Arrow, Iceberg, delta-rs, vector stores, storage buckets).
- Clear written and verbal communication skills.
- Team-first mindset and high degree of autonomy and ownership.
- Passion and curiosity for AI-assisted software development workflows
- Based in Berlin and open to working onsite regularly (3-4 days per week).
🎯 Nice to Have
- Experience building developer-facing APIs, SDKs, or tooling.
- Data Platform/Platform engineering experience (e.g. Docker, GitHub Actions, Kubernetes, AWS/GCP) or frontend engineering experience.
- Hands-on experience with data platforms like Snowflake, BigQuery, Databricks, or Iceberg.
- Contributions to open-source projects.
Benefits
In our work culture, we value each other’s autonomy and efficiency. We have set hours for communication and deep work. We like automation, so we automate our work before we automate the work of others.
- We are an office-first company but give you plenty of opportunities for deep work and work from home. Dedicated "no meeting days" to help the team focus on their most impactful work.
- As we mostly work from the Berlin office, we cover your public transportation ticket.
- We are deeply committed to your personal and professional growth, and as such, we allocate an annual budget for learning and development.
- We offer regular subsidized team lunches.
- Urban Sports Club membership.
- For roles that contribute directly to shaping our product and company, we offer an ESOP plan, tailored to each employee’s role and level of commitment.
Top Skills
What We Do
Since 2017, the number of Python users has been increasing by millions annually. The vast majority of these people leverage Python as a tool to solve problems at work. Our mission is to make them autonomous when they create and use data in their organizations. For this end, we are building an open source Python library called data load tool (dlt).
Our users use dlt in their Python scripts to turn messy, unstructured data into regularly updated datasets. It empowers them to create highly scalable, easy to maintain, straightforward to deploy data pipelines without having to wait for help from a data engineer.
We are dedicated to keeping dlt an open source project surrounded by a vibrant, engaged community. To make this sustainable, dltHub stewards dlt while also offering additional software and services that generate revenue (similar to what GitHub does with Git).
dltHub is based in Berlin and New York City. It was founded by data and machine learning veterans. We are backed by Dig Ventures and many technical founders from companies such as Hugging Face, Instana, Matillion, Miro, and Rasa
