Quant Data Engineer: Real-Time Modelling & Data Quality

Pythia Sports; London; Hybrid; NOK 1,014,000 - 1,521,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Cycle to work

Enhanced parental leave

Enhanced sick pay

Increased holiday allowance

Career development

Job summary

Pythia Sports is expanding its Quant Data Engineering team in London, offering a hybrid work model with 2 days in the office. You will partner with quant modellers to deliver reliable, well-structured data for research, modelling and analysis.

The role focuses on data quality, building robust Python-based data workflows, and improving data flows across engineering and operations to support predictive sports modelling.

Qualifications

• Strong Python experience for data processing, investigation and workflow development.
• Excellent SQL skills and strong experience with relational databases (PostgreSQL preferred).
• Proven experience building and maintaining data pipelines in production environments.
• Experience with analytical data warehouses such as ClickHouse, BigQuery, Snowflake or Redshift.
• Ability to turn messy, evolving datasets into reliable assets for downstream modelling.

Responsibilities

• Prepare, refine and maintain datasets used for research, modelling and analysis.
• Improve the structure, quality and usability of underlying data for quant workflows.
• Investigate data issues, identify root causes and collaborate with relevant teams to resolve them.
• Develop repeatable data preparation processes to improve reliability and consistency.
• Review existing and new data sources to determine suitability and improvements.

Skills

Python

SQL

Data pipelines

Data quality

Tools

ClickHouse

BigQuery

Snowflake

Redshift

GitLab

Jira

Confluence

Job description

Pythia Sports is expanding its Quant Data Engineering team in London, offering a hybrid work model with 2 days in the office. You will partner with quant modellers to deliver reliable, well-structured data for research, modelling and analysis.

The role focuses on data quality, building robust Python-based data workflows, and improving data flows across engineering and operations to support predictive sports modelling.