Data engineer (Python)

Our stack: Python 3 (asyncio), Airflow, Docker, PostgreSQL/TimescaleDB, GitLab, Metabase, Streamlit, RabbitMQ, Kubernetes, AWS (S3, EC2) and we're also playing around with ClickHouse, Apache Iceberg, DuckDB, and Trino.

We're Quantlane, a proprietary trading firm built for traders. Our goal is to create a best-in-class ecosystem that helps traders unlock their full potential. A key part of that is our data platform — providing all kinds of data that traders (and their algos) rely on to make trading decisions

👨‍💻 How we work

Our development team has 16 people. We work in an agile environment, develop iteratively, and take testing seriously. We have dedicated communities focused on different domains — Data, DevOps, Execution Platform, On-call/Support, and Trading Tooling, among others.

📊 Who we're looking for

This role is for our Data team, which currently has five Data Engineers and one Data Scientist. We tackle interesting data challenges here — our goal is to make sure data is in the right quality, format, and place at the right time.

🔥 Want to help build a data platform that has a real impact on our traders' success? Come join us! 🚀

What your day-to-day will look like

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• Building Python applications that process data (pandas, asyncio)
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• Contributing to the design and improvement of the data platform
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• Developing backend applications in Python (asyncio, RabbitMQ)
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• Deploying those applications to production (Airflow, Kubernetes)
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• Talking to traders and analysts (your internal customers) about the features they need
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• Taking turns with the rest of the team on platform support

What we offer

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• Snacks, 5 weeks of vacation, 5 sick days, and a Multisport card

• Brand new, modern offices in Karlín

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• Hybrid setup — ideally 3 days on-site
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• Regular sessions with a company therapist / coach
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• English lessons with a native speaker
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• Internal training and contributions toward technical conference

A bit about you

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• You have experience working with Data Lake, Lakehouse, and Streaming data concepts
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• You've built applications that process data — both historical and real-time
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• You know SW development best practices (Git, testing)

Ideally, you also

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• Have hands-on experience with Apache Iceberg, Trino/AWS Athena, or ClickHouse
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• Are comfortable with data libraries like pandas/polars
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• Know your way around ETL workflow tools like Apache Airflow
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• Have solid SQL skills, ideally PostgreSQL
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• Know Python asyncio
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• Have an interest in capital markets