Market Data Quality Analyst

Your Core Responsibilities

• Acquire, clean, and maintain reference data, corporate actions data and alternative data from various sources (exchanges, third-party vendors, proprietary feeds).
• Design and own automated Python pipelines for ingestion, transformation and publication of these sources.
• Analyse datasets using SQL, Pandas and Polars to help model, investigate issues, and document data.
• Monitor and resolve data anomalies, missing values, and inconsistencies to ensure high data quality and develop automated testing strategies to flag such issues.
• Work with engineers to enhance data storage, retrieval, and efficiency for research workflows.
• Work with researchers, traders and other data users to turn data needs into well-defined, maintained datasets.

Your Skills and Experience

• 5+ years in a data-focused role, preferably in a trading, quantitative finance, or financial services environment.
• Strong Python including data processing frameworks such as Pandas or Polars.
• Advanced SQL for analysing large datasets efficiently.
• Genuine interest in how exchanges work – including instrument lifecycles, session structures, holiday calendars and symbology.
• Eagerness to get into the details of a dataset, either to find quality issues or to help document data edge cases.
• Strong communication skills and the ability to work cross-functionally with researchers, traders and engineers to build up data requirements.
• Nice to have: visualisation tools (Streamlit, Plotly), distributed processing (Spark, Dask), CI/CD, Kubernetes.

About Us