Data Engineer, Fraud

Das ist der Job

The position emphasizes building scalable, high-performing data pipelines and storage systems for fraud use cases.

Darum lohnt es sich

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. 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. Create fraud-specific datasets and features to enhance detection accuracy while supporting business and analytics teams. Partner with data, product, and engineering teams to proactively address fraud trends.

Benefits Annualised rate of €98,000 with a retention bonus scheme paid every 6 months based on tenure. Events and gatherings throughout the year, including team gatherings and cultural events. About Xcelirate 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.

Position Overview The Data Engineer will focus on designing, developing, and maintaining robust data infrastructure to support use cases such as fraud detection as well as general data engineering.

Although this role involves light integration with machine learning models, its primary responsibility is creating the technical foundation that powers fraud detection, analytics and reporting. Responsibilities Develop and maintain efficient, scalable data pipelines for fraud detection.

Design and optimise data storage solutions for analysing fraud signals and managing historical data. Monitor fraud data pipelines to ensure system reliability and troubleshoot performance issues. Establish and document best practices for fraud-related data engineering.

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 such as Apache Airflow and DBT.

Strong knowledge of database design, query optimisation, and ETL/ELT workflows, ideally including relational databases such as MySQL and columnar databases such as ClickHouse. Experience building and maintaining production data pipelines.

Familiarity with leveraging machine learning models as a component of the broader data pipeline, including model registries such as MLflow. Understanding of CI/CD processes for data pipelines. Hands‑on experience with data visualization platforms for trend reporting 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. Top‑Notch workstation: latest MacBook and branded merchandise for an optimal work environment.

Global co‑working access to maintain work‑life flexibility. Full flexibility in work location and hours to support work‑life balance. 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!

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. #J-18808-Ljbffr