Overview

We’re looking for a Data Engineer to help us build and maintain reliable, scalable data workflows that power our trade surveillance platform.

Responsibilities:
  • Build, maintain, and customize ETL pipelines that process large volumes of data on a daily basis
  • Investigate data processing issues and resolve them
  • Collaborate directly with clients to gather requirements, provide updates, and ensure successful delivery of data workflows
Nice To Have:
  • Kubernetes & Docker: ability to explore a cluster, inspect pods/containers
  • Experience working with Apache Airflow (especially for managing data processing pipelines)
  • Basic knowledge of financial markets and trading workflows: common asset classes (e.g., equities, derivatives, fixed income), trade lifecycle events, and corporate actions
Required Qualifications:
  • Linux: confident with the command line and system fundamentals
  • GitLab / Git: working knowledge of Git, understanding of core branching strategies (Git Flow, GitHub Flow, GitLab Flow) and main git commands
  • Python: hands-on experience with Python and main tools for data manipulation: Pandas, Numpy, working with datetimes, string transformations
  • English: professional working proficiency (spoken and written)
Benefits:
  • Flexible working arrangements: full remote, hybrid, or office-based, depending on your location and preferences
  • Competitive compensation, aligned with your experience, skillset, education, and local market standards
  • Regular performance reviews linked to salary adjustments
  • Medical insurance for you and immediate family members
  • Professional-development budget to support courses, certifications, and conferences
  • Supportive international team
Note:

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