Quant Data Engineer

🕒 April 10

Apply Now

Find Similar Remote Jobs

Receive Emails For Remote Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Pythia Sports

WebsiteLinkedInAll Job Openings

11 - 50 employees

⚽ Sports

🎲 Gambling

🤝 B2B

Sports • Gambling • B2B

Pythia Sports is a data-driven sports analytics and wagering services firm founded in 2014 that builds proprietary predictive models and automated trading and risk-management systems for betting operators and private clients worldwide. The company provides automated risk management (ARM), algorithmic trading, data acquisition and processing, and machine-learning-based performance prediction, including a bloodstock (racehorse) analytics offering. Pythia works closely with a small number of institutional clients to deliver pricing, execution software, and ongoing global trading operation support.

📋 Description

• Work day-to-day with quant modellers to prepare, refine and maintain datasets used for research, modelling and analysis • Help improve the structure, quality and usability of underlying data so that it can be consumed efficiently by quant workflows • Investigate data issues affecting modelling outputs, identifying root causes and working with relevant teams to resolve them • Support the development of repeatable data preparation processes that make research datasets more reliable, consistent and easier to work with • Build and maintain Python-based data workflows and supporting pipelines for ingestion, transformation and validation of modelling data • Maintain and further develop Pythia’s historical data assets, ensuring they remain accurate, accessible and fit for analytical use • Work with engineers to improve upstream and downstream data flows, helping ensure that critical data is captured and processed effectively • Support data migrations, backfills and structural improvements where required to improve the usefulness and reliability of modelling datasets • Contribute to the development of tooling and processes that make it easier to explore, prepare and troubleshoot data used by the quant team • Ensure data quality and integrity through validation, reconciliation and targeted monitoring across key datasets • Expand visibility into data issues by improving checks, alerts and investigative workflows across critical pipelines and sources • Define and improve data logic, transformations and assumptions, ensuring they are clearly documented and consistently applied across datasets • Improve the clarity and usability of data through better documentation, metadata management and standardisation of definitions • Work closely with engineering and operational teams to resolve anomalies, gaps and inconsistencies in source data • Contribute to the ongoing evolution of Pythia’s data capabilities, balancing immediate modelling needs with longer-term improvements to data quality and maintainability

🎯 Requirements

• Strong experience in a Quant Data Engineer, Research Data Engineer or similar role working with complex datasets • Strong Python experience for data processing, investigation and workflow development • Excellent SQL skills and strong experience working with relational databases, preferably PostgreSQL • Proven experience preparing, transforming and validating datasets for analytical, modelling or research use cases • Strong experience investigating data issues and tracing problems through pipelines, transformations and source systems • Experience building and maintaining data pipelines or processing workflows in production environments • A strong understanding of data quality, reconciliation and validation practices • Experience working closely with technical stakeholders to understand how data is consumed and how it can be improved • Confidence working with messy, incomplete or evolving datasets and turning them into reliable assets for downstream users • Experience with analytical data warehouse technologies such as ClickHouse, BigQuery, Snowflake, Redshift or similar would be beneficial • Experience with version control systems (preferably GitLab) and working with tools such as JIRA & Confluence • Experience working in Agile environments and collaborating with distributed teams • Ability to work well in a dynamic, fast-paced environment and quickly adapt to new technologies and requirements • A passion for detail and problem solving, with excellent verbal and written communication skills

🏖️ Benefits

• Private health and dental insurance • Cycle to work scheme • Enhanced parental leave • Enhanced sick pay • Increased holiday allowance • Plenty of career development opportunities