Data Engineer

Location Amsterdam
Discipline: Financial Technology
Job type: Permanent
Contact name: Lewis Piper

Contact email: lewis.piper@venturesearch.com
Job ref: 2564
Published: about 2 months ago
Venture Search is working with a Commodities proprietary trading firm based in Amsterdam that is recruiting for a Data Engineer to join their team. The successful incumbent will sit within a high-performance team, working alongside some of the industry's best quantitative analysts, strategists, data scientists, and traders.

Your Responsibilities
  • Design, build, and maintain robust data pipelines for real-time trading applications.
  • Manage and optimise Data Lakes and data warehousing solutions.
  • Support development and deployment of ML/AI Model, using MLOps best practices
  • Oversee data collection processes and ensure high standards of data integrity.
  • Employ automation to enhance data processes and system efficiency.
  • Develop and maintain scalable data pipelines to support real-time decision-making.
  • Manage the storage and accessibility of data in Data Lakes and warehousing systems.
  • Implement automation strategies to improve data integrity and processing.
  • Collaborate with Software Engineers and other Data Engineers on diverse projects to enhance trading systems.
Qualifications
  • Deep knowledge of programming languages such as Java, C# and/or C++ and developing application in Python
  • Significant experience working with modern data technologies, like Postgres, Timescale dB, Quest dB, MongoDB, Kafka/Event Hub
  • Acquaintance in deploying and managing microservices with docker, Kubernetes and bash scripting
  • Expert knowledge of Azure, AWS or GCP and management of large-scale data pipeline system
  • Desired capabilities with MLOps Frameworks like Kubeflow, MLFlow, Databrick ML tools, etc
  • Experience with Databricks, Data Lakes, and workflow orchestration tools like Dagster or Airflow.
  • Problem solver oriented with a keen interest in environmental sustainability and technological innovation.
  •  Familiarity with automated trading systems and real-time data streaming for high-frequency trading, is beneficial but not mandatory.