Data Engineer, Fraud

Xcelirate
London
1 week ago
Applications closed

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This range is provided by Xcelirate. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

Who Are We?

Xcelirate develops technologically-advanced platforms which are accessed by thousands of users every minute! We are proud to offer a workplace where the sharpest developers come together to strategically plan and swiftly execute practices which see us maintain our existing market dominance and attain global expansion. We owe our success to our customers who have seen us grow across a decade, and our talented team who have made that growth possible.

What are we looking for?

A Data Engineer, experienced in Fraud data:

  • Design, develop, and maintain robust data infrastructure to support use cases such as fraud detection but also general data engineering.
  • Build scalable, high-performing data pipelines and storage systems for fraud use cases
  • Create the technical foundation that powers such use cases of fraud detection, analytics and reporting

What will you be doing?

  • Develop and Maintain Pipelines: build and maintain efficient, scalable data pipelines for use cases such as fraud detection
  • Support Fraud Analytics: enable analysts and product teams to identify and address emerging fraud patterns through engineered datasets
  • Integrate Detection Models: collaborate with teams to operationalise external fraud detection models and integrate them into the data infrastructure
  • Data Storage Optimisation: design and optimise data storage solutions for analysing fraud signals and managing historical data
  • Feature Engineering: create fraud-specific datasets and features to enhance detection accuracy while supporting business and analytics teams
  • Pipeline Monitoring and Optimisation: monitor fraud data pipelines to ensure system reliability and troubleshoot performance issues
  • Best Practices Documentation: establish and document best practices for fraud-related data engineering
  • Cross-Team Collaboration: partner with data, product, and engineering teams to proactively address fraud trends

Requirements

What will you bring along?

  • 5+ years of experience as a data engineer with some expertise in fraud detection systems or similar
  • Proficiency in Python and SQL, with knowledge of orchestration tools (e.g., Apache Airflow, DBT)
  • Strong knowledge of database design, query optimisation, and ETL/ELT workflows
  • Familiarity with leveraging machine learning models, primarily as a component of the broader data pipeline
  • Understanding of CI/CD processes for data pipelines
  • Hands-on experience with data visualization platforms for trend reporting (e.g., Tableau, Superset, Metabase)
  • Familiarity with statistical techniques for fraud trend analysis and reporting
  • Experience with Git and version control in collaborative workflows

We are always looking for the best candidates, so if you think you would be a good fit even if you don't meet 100% of the requirements, we would love to hear from you!

Benefits

How We Support Our Contractors:

  • Gross Annual Compensation: €80,000
  • Top-Notch Workstation: We provide the latest MacBook, branded merchandise, and everything you need for an optimal work environment.
  • Global Co-Working Access: Work from a global network of co-working spaces to keep your work-life dynamic and flexible.
  • Flexibility: Enjoy full flexibility in work location and hours, supporting a work-life balance tailored to your needs.
  • Events and Gatherings: Participate in exciting events throughout the year, including team gatherings, cultural events, and other fun activities

At Xcelirate, we're committed to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We pride ourselves in being an equal opportunity workplace.Seniority level

  • Seniority levelMid-Senior level

Employment type

  • Employment typeFull-time

Job function

  • Job functionAnalyst
  • IndustriesIT Services and IT Consulting

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