--- title: 'Data engineer (Python) at Quantlane' canonical: 'https://feeny.ai/job/data-engineer-python-quantlane-prague-p01bephn3pnt' type: 'job' last_seen: '2026-11-05' --- # Data engineer (Python) at Quantlane - **Company:** Quantlane - **Location:** Prague, Czech Republic - **Employment:** full-time - **Work type:** hybrid - **Posted:** 2025-03-26 - **Last confirmed live:** 2026-11-05 - **Apply:** https://jobs.lever.co/quantlane/55d1323f-0d1e-42ac-8be8-62b785746e8b ## Job description 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: - Building Python applications that process data (pandas, asyncio) - Contributing to the design and improvement of the data platform - Developing backend applications in Python (asyncio, RabbitMQ) - Deploying those applications to production (Airflow, Kubernetes) - Talking to traders and analysts (your internal customers) about the features they need - Taking turns with the rest of the team on platform support What we offer: - Snacks, 5 weeks of vacation, 5 sick days, and a Multisport card - Brand new, modern offices in Karlín - Hybrid setup — ideally 3 days on-site - Regular sessions with a company therapist / coach - English lessons with a native speaker - Internal training and contributions toward technical conference A bit about you: - You have experience working with Data Lake, Lakehouse, and Streaming data concepts - You've built applications that process data — both historical and real-time - You know SW development best practices (Git, testing) Ideally, you also: - Have hands-on experience with Apache Iceberg, Trino/AWS Athena, or ClickHouse - Are comfortable with data libraries like pandas/polars - Know your way around ETL workflow tools like Apache Airflow - Have solid SQL skills, ideally PostgreSQL - Know Python asyncio - Have an interest in capital markets ## About Quantlane ## Company Overview - **One-liner**: Quantlane is a proprietary trading firm that combines systematic precision with discretionary insight to trade across global capital markets. - **Entity Type**: Private (bootstrap-stage, no external funding disclosed) - **Headquarters**: Prague, Czechia - **Founded**: 2014 - **Founders**: Lukas Hnizdo (Partner & Co-Founder) – other co-founders not publicly listed ## Core Business - **Primary industry**: Proprietary trading / capital markets - **Target customers**: Internal traders (the firm trades its own capital; not a client-facing broker) - **Mission**: “One House. Two Styles. One Edge. By uniting discretionary insight with systematic precision, we turn data into scalable edge.” [quantlane.com](https://quantlane.com/about) ## Products & Services - **Proprietary Trading Platform**: A technology stack built in-house that supports both discretionary and systematic trading strategies across multiple venues and asset classes globally. The platform covers research, monitoring, risk management, compliance, and large-scale execution. [quantlane.com](https://quantlane.com/who-we-are) ## Market Standing - **Valuation**: Not disclosed - **Key Metric**: Annual Revenue – not publicly available (private firm); Total Funding – none known (bootstrapped) - **Notable Investors/Partners**: No external investors identified; the firm is privately held - **Growth Signals**: - Headcount grew 40% year-over-year to 26 employees (as of early 2026) [linkedin.com](https://linkedin.com/company/quantlane) - Offices in Prague (HQ), Switzerland, and Spain - Technical staff makes up 34% of the workforce, indicating a strong engineering focus - LinkedIn follower base grew 42.4% year-over-year to ~1,250 ## Competitive Advantages - **Hybrid trading approach**: Unifying discretionary (human judgment) and systematic (algorithmic) trading under one roof, a rare combination that allows for diversified edge. - **Technology-driven culture**: Heavy investment in Python, Django, Kubernetes, PostgreSQL, and monitoring tools (Grafana, Prometheus, ELK) – a tech stack typical of high-frequency / quantitative firms. - **Flat, autonomous environment**: Employees are given responsibility and trust to make decisions with calculated risk. [quantlane.com](https://quantlane.com/career) - **Prague base with global reach**: Low-cost, high-talent location in Europe with access to global markets. ## Strategic Focus - **Grow capital, grow talent, enjoy the journey**: The firm explicitly states that its edge is its people. Current priorities include hiring a Head of Data / Trading Data Platform lead and expanding the engineering and research teams. [linkedin.com](https://linkedin.com/company/quantlane) and [jobs.lever.co](https://jobs.lever.co/quantlane) - **Scaling systematic edge**: Continued investment in data infrastructure and algorithmic research to turn data into scalable trading advantages. ## Why Work Here - **Culture**: Collaborative, trust-based environment where employees are empowered to take ownership. The firm emphasises “calculated risk” and learning. - **Hybrid work**: Roles in Prague are hybrid (office + remote). Global team operates as one unit across time zones. - **Tech-forward**: Engineers work with modern tools (Python, Kubernetes, Airflow, React) and are involved in the full trading lifecycle. - **AI in hiring**: The recruitment process may use AI tools to review applications, but final decisions are made by humans. [jobs.lever.co](https://jobs.lever.co/quantlane) - **Diverse team**: Mix of traders, quants, and developers; 11% of employees are in research roles. - **Perks**: Not explicitly listed, but the small, growing size (26 people) suggests high impact and visibility. ## Sources 1. [Quantlane About Page](https://quantlane.com/about) 2. [Quantlane Who We Are](https://quantlane.com/who-we-are) 3. [Quantlane Careers](https://quantlane.com/career) 4. [Quantlane LinkedIn](https://linkedin.com/company/quantlane) 5. [Quantlane Jobs on Lever](https://jobs.lever.co/quantlane) ## Other roles at Quantlane - [Senior Python developer](https://feeny.ai/job/senior-python-developer-quantlane-prague-s2nyv2z6dns7) — Prague, Czech Republic