Data Platform Engineer - Python @ Grafton Recruitment

Data Platform Engineer - Python @ Grafton Recruitment

Polsko

• Strong programming experience in Python and good command of shell scripting
• Solid grasp of data engineering principles, including ETL pipelines and time-series data manipulation
• Proficiency in Linux-based systems, with knowledge of networking and system performance analysis
• Experience with containerized and orchestrated environments (e.g., Docker, Kubernetes)
• Familiarity with CI/CD pipelines and infrastructure-as-code practices
• Understanding of monitoring and metrics systems (such as Grafana, Prometheus, or ELK stack)
• Motivation to build scalable, high-performance systems supporting research and trading applications

Nice to have:

• familiarity with cloud-based data solutions (for example, AWS ECS/EKS or equivalent technologies)

An international organization operating within the financial technology and trading industry is looking for a Data Platform Engineer to strengthen its technical team. The company leverages advanced analytics, large-scale data, and modern infrastructure to support systematic trading and research activities across global markets. Collaboration between engineers and researchers is central to its culture, which emphasizes innovation, technical excellence, and continuous improvement.

Role Overview

You will be part of a team responsible for the systems that enable data-driven trading strategies. The position focuses on developing and maintaining tools and infrastructure used for large-scale data processing, monitoring, and system automation. The role involves close cooperation with research and engineering teams to ensure stable, high-performance, and low-latency operations.

What’s Offered

You’ll join a team that values technical depth, collaboration, and innovation. The company encourages open communication, respect, and diversity of perspectives. Alongside professional growth opportunities, employees benefit from initiatives supporting a balanced and healthy work life.

,[Design and implement systems for collecting, processing, and managing large-scale market and internal datasets., Build and maintain data pipelines and services to ensure performance, reliability, and data integrity., Develop frameworks for monitoring, alerting, and observability for data systems and compute infrastructure., Collaborate with engineers and researchers to integrate data delivery and compute workflows into production environments., Enhance CI/CD and infrastructure automation to streamline deployment and operations of data systems., Develop expertise in distributed computing, data storage architectures, and system performance engineering over time.] Requirements: Python, Shell, Data engineering, ETL, Linux, Networking, Grafana, Prometheus, ELK, AWS, ECS, EKS Additionally: Sport Subscription, Private healthcare, International projects.

Kategorie

data

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