Data Engineer (Python) at Quantlane | Prague
QuantlanePrague
On-site Full-time
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Experience Level
Experience
Qualifications
Qualifications:Proficient in Python, particularly with asyncio. Experience with data pipelines and workflow orchestration (e.g., Airflow). Familiarity with containerization (Docker) and cloud services (AWS). Knowledge of databases, specifically PostgreSQL/TimescaleDB. Experience with GitLab for version control. Strong problem-solving skills and a collaborative mindset.
Our Tech Stack: Python 3 (asyncio), Airflow, Docker, PostgreSQL/TimescaleDB, GitLab, Metabase, Streamlit, RabbitMQ, Kubernetes, AWS (S3, EC2), and we also explore ClickHouse, Apache Iceberg, DuckDB, and Trino.
We are Quantlane, a proprietary trading firm designed for traders. We operate a diversified portfolio of systematic and discretionary strategies across equities, futures, energy, and commodities. A key aspect of our company is our data platform, which provides various data that our traders (and their algorithms) rely on for their trading decisions.
Our Working Style
Our development team consists of 16 members, working in an agile environment where we focus on iterative development and emphasize testing. We currently have three specialized product sub-teams , Execution, Data, and Infrastructure , each concentrating on the development and operation of our core domains.
Who We Are Looking For
We are seeking a new member for our Data team, which currently includes five data engineers and one data scientist. Here, we tackle intriguing data challenges, ensuring that data is delivered in the required quality, format, and time to the desired location.
Do you want to contribute to the development of a data platform that has a real impact on the success of our traders? Join us!
About Quantlane
Quantlane is an innovative proprietary trading firm that specializes in providing traders with a robust data platform. Our diverse strategies across multiple asset classes help traders make informed decisions, fostering a culture of excellence and continuous improvement in trading performance.
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