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We are looking for an enthusiastic Solutions Engineer to help our customers implement our products in their systems, as well as assist our sales team in winning customers. If you thrive in the fast-paced environment of a small team and are excited about playing a pivotal role in shaping the product of an early-stage startup, then this opportunity is made for you.
We are dltHub, a creator of dlt - the most popular open-source library for data loading in Python with over 3 million monthly downloads. dlt is the “EL” layer of ELT: it extracts and loads data from any source into clean, typed datasets. Developers love it because it’s modular, LLM-friendly, and lets them create new connectors in minutes.
Building on this foundation, we’re now developing dltHub - a next-generation data engineering platform built on top of dlt. dltHub combines the Pythonic simplicity of dlt with enterprise-grade compliance, security, and scalability. It provides everything needed for modern data engineering, including transformations, data quality, managed runtimes, flexible storage options, observability, and agentic tooling - empowering developers to go from local experiments to production with a single command.
We’re headquartered in Berlin and expanding across North America (Montreal → San Francisco → NYC). Our team brings deep experience in data infrastructure, machine learning, and developer tooling backed by Bessemer Venture Partners, Foundation Capital, Dig Ventures, and technical founders from Hugging Face, Metaflow, LanceDB, MotherDuck, Datadog, Mode, and Rasa.
Our culture is rooted in engineering principles: speak with courage · build what matters · automate relentlessly · deliver on commitments · win together
The solutions engineering team both manages post-sales activities and contributes to pre-sales activities. You will be a key member of this team, performing tasks like:
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.
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