Xcelirate

Xcelirate

Xcelirate is a global technology innovator in the online entertainment industry, providing cutting-edge solutions for low latency, tight security, and exceptional user experiences. With a focus on helping users find connections safely, Xcelirate operat...

Internet Software & Services
11-50
Founded 2009

Description

  • Design, build, and maintain scalable data pipelines for fraud detection and general data engineering use cases.
  • Support fraud analytics by delivering engineered datasets that help analysts and product teams identify emerging fraud patterns.
  • Collaborate with teams to operationalise external fraud detection models and integrate them into the data infrastructure.
  • Design and optimise data storage solutions for fraud signal analysis and historical data management.
  • Create fraud-specific datasets and features to improve detection accuracy and support business and analytics needs.
  • Monitor data pipelines, troubleshoot performance issues, and maintain system reliability.
  • Establish and document best practices for fraud-related data engineering.
  • Partner with data, product, and engineering teams to proactively address fraud trends.
  • Contribute to the broader data foundation that powers fraud detection, analytics, and reporting.

Requirements

  • 3+ years of experience as a data engineer, ideally with some experience in fraud detection systems or similar domains.
  • Strong proficiency in Python and SQL.
  • Experience with orchestration and transformation tools such as Apache Airflow and DBT.
  • Strong knowledge of database design, query optimisation, and ETL/ELT workflows.
  • Experience with relational databases such as MySQL and columnar databases such as ClickHouse.
  • Experience building and maintaining production data pipelines.
  • Familiarity with leveraging machine learning models within data pipelines, including model registries such as MLflow.
  • Understanding of CI/CD processes for data pipelines.
  • Hands-on experience with data visualisation platforms such as Tableau, Superset, or 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.

Benefits

  • Annualised rate of €98,000.
  • Retention bonus scheme paid every 6 months based on time with the company.
  • Latest MacBook, branded merchandise, and other equipment for an optimal work environment.
  • Access to a global network of co-working spaces.
  • Full flexibility in work location and hours.
  • Team gatherings, cultural events, and other company events throughout the year.
  • Equal employment opportunity across all protected characteristics.

Interested in this position?

Apply directly on the company website

Apply Now

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