Data Engineer - Quantitative Analysis

BettingJobs is seeking a Data Engineer to join a small but growing quant team in the sports betting industry. Working alongside the modelling team, you will be responsible for ensuring they have access to reliable, well-structured and high-quality data for research, modelling and analysis. From building robust Python-based workflows to investigating complex data issues and assessing new data sources, the Data Engineer will be responsible for extracting maximum value from the data. Responsibilities: Work day-to-day with quant modellers to prepare, refine and maintain datasets used for research, modelling and analysisInvestigate data issues affecting modelling outputs, identifying root causes and working with relevant teams to resolve themBuild and maintain Python-based data workflows and pipelines for ingestion, transformation and validation of modelling dataMaintain and develop historical data assets, ensuring they remain accurate, accessible and fit for analytical useWork with engineers to improve upstream and downstream data flows, ensuring critical data is captured and processed effectivelyEnsure data quality and integrity through validation, reconciliation and targeted monitoring across key datasetsExpand visibility into data issues by improving checks, alerts and investigative workflows across critical pipelinesDefine and improve data logic, transformations and assumptions, ensuring they are clearly documented and consistently appliedSupport data migrations, backfills and structural improvements to improve the reliability of modelling datasetsContribute to tooling and processes that make it easier to explore, prepare and troubleshoot data used by the quant team

Strong experience in a Quant Data Engineer, Research Data Engineer or similar role working with complex datasetsUnderstanding of the sports betting industryStrong Python skills for data processing, investigation and workflow developmentExcellent SQL skills and solid experience with relational databases, preferably PostgreSQLProven experience preparing, transforming and validating datasets for analytical, modelling or research use casesExperience investigating data issues and tracing problems through pipelines, transformations and source systemsExperience building and maintaining data pipelines or processing workflows in production environmentsStrong understanding of data quality, reconciliation and validation practicesExperience working with analytical data warehouse technologies such as ClickHouse, BigQuery, Snowflake or Redshift (beneficial)Experience with version control systems (preferably GitLab) and tools such as JIRA and ConfluenceComfortable working with messy, incomplete or evolving datasets and turning them into reliable assetsExperience working in Agile environments and collaborating with distributed teamsExcellent attention to detail, strong problem-solving ability and clear verbal and written communication skills