Python Data Engineer – Market Microstructure Analytics

Required:

• Minimum of 7+ years of experience in Python development, building libraries, data platforms, or analytical tooling.
• Strong expertise working with large-scale, time-series datasets using NumPy, Pandas, and SQL.
• Experience processing exchange protocols, order flow, and high-frequency trading data.
• Solid knowledge of SQL and analytical databases such as Snowflake, ClickHouse, Redshift, BigQuery, Druid, or Databricks.
• Ability to translate complex analytical or trading problems into robust engineering solutions.
• Familiarity with Linux environments, software engineering best practices, testing, version control, and CI/CD.
• Excellent communication skills for working effectively with technical and non-technical stakeholders.
• Fluent English, spoken and written.

Nice to have:

• Exposure to low-level programming languages such as C, C++, or Rust.
• Understanding of network protocols, packet analysis, or performance optimization techniques.
• Previous experience in electronic trading, execution analysis, or market microstructure.

Data engineering and analytics:

• Develop and maintain Python libraries, data pipelines, and tooling to process exchange protocols, order flow, and large-scale trading datasets.
• Analyze trading behavior across venues to identify execution inefficiencies, latency issues, and fill performance gaps.
• Build analytical frameworks, metrics, and monitoring tools to evaluate execution quality and system performance.
• Support live trading systems through data validation, pipeline reliability, and real-time monitoring.
• Collaborate with stakeholders to translate analytical insights into actionable improvements in execution strategies.
• Work with research and infrastructure teams to advance understanding of market behavior and tools for ongoing development.

• Candidates must have an existing legal right to work in Europe; candidates without valid work authorization are not considered.