Data Engineer, Fraud

Stack

Responsibilities

• ▹Build and maintain efficient, scalable data pipelines for fraud detection
• ▹Enable analysts and product teams to identify and address emerging fraud patterns through engineered datasets
• ▹Collaborate with teams to operationalise external fraud detection models and integrate them into the data infrastructure
• ▹Design and optimise data storage solutions for fraud signals and historical data
• ▹Create fraud-specific datasets and features to enhance detection accuracy
• ▹Monitor fraud data pipelines to ensure reliability and troubleshoot performance issues
• ▹Establish and document best practices for fraud-related data engineering
• ▹Partner with data, product, and engineering teams to address fraud trends

Requirements

• ▹3+ years of experience as a data engineer, with expertise in fraud detection systems or similar
• ▹Proficiency in Python and SQL, with knowledge of orchestration and transformation tools (e.g. Apache Airflow, DBT)
• ▹Strong knowledge of database design, query optimisation, and ETL/ELT workflows, including relational (MySQL) and columnar (ClickHouse) databases
• ▹Experience building and maintaining production data pipelines
• ▹Familiarity with leveraging ML models as part of the data pipeline, including model registries such as MLflow
• ▹Understanding of CI/CD processes for data pipelines
• ▹Hands-on experience with data visualization platforms (e.g. Tableau, Superset, Metabase)
• ▹Ability to support model serving components such as Flask or FastAPI
• ▹Familiarity with statistical techniques for fraud trend analysis and reporting
• ▹Experience with Git and version control in collaborative workflows

What we offer

• ▹Annualised rate of €98,000 plus a retention bonus scheme, paid every 6 months based on tenure
• ▹Latest MacBook and branded merchandise provided as workstation

About the company

Xcelirate develops technologically advanced platforms accessed by thousands of users every minute, with a decade-long track record of growth.