Data Analytics Engineer II - Fraud

The goal of the Fraud team is to proactively protect, prevent, detect and respond to fraudulent behavior. The team is responsible for managing security and fraud threats across the business globally. Continuous improvement on detection and response capabilities is key. The Fraud team is part of the Security department within the Central Technology department. In this role, you work closely with the Supplier Fraud Analytics Team, Product Managers, Analytics and Engineering managers.

Drive the implementation of reliable and well trusted metrics defined by the business, connecting disparate datasets into unified data products in the Lakehouse and/or Data Warehouse. Produce curated, reusable analytical data products to enable self-serve analytics for many internal customers across departments. Enter a new area, own the quality of the data and work with product owners and scientists to develop the analytics backlog. Model data following best practices and Data Warehousing methodologies such as Data Vault and (Kimball) Dimensional modeling. Transform large, complex data sets into pragmatic, actionable insights and provide them in a consumable format for historical or predictive analysis. Perform Data Governance responsibilities such as technical stewardship, data classification, compliance management, data quality monitoring, and security considerations. Build data visualizations to trial/validate data products you build before releasing to customers. Maintain and tune data pipeline health, including troubleshooting issues

Minimum of 3+ years of experience in a data or software-adjacent field, working with systems and data infrastructure at scale. Experience in designing and implementing mature Data Warehouse pipelines using dimensional modeling methodologies. Highly skilled at writing and maintaining high-quality and reusable code, applying design patterns and meeting coding standards. Experience working in a DevOp /DataOps environment. Experience with ELT/ETL tools and methodologies. Experience using scheduled workflow management tools such as Apache Airflow or Argo. Experience/Expertise with relational databases and any flavour of SQL in an analytical context. Experience with data exploration/visualisation and data story telling. Excellent communication (written and spoken) and stakeholder management.

Annual paid time off and generous paid leave scheme including: parental (22-weeks paid leave), grandparent, bereavement, and care leave Hybrid working including flexible working arrangements, working from home furniture and ergonomic support, and up to 20 days per year working from abroad (home country) A beautiful sustainable HQ Campus in Amsterdam, that offers on-site meals, coffee, and snacks, multi-faith and breastfeeding rooms at the office Commuting allowance and bike reimbursement scheme Discounts & Wallet credits to spend on our products, upgrade to Booking.com Genius Level 3, and friends & family Booking.com discount vouchers Free access to online learning platforms, development and mentorship programs Global Employee Assistance Program, free Headspace membership DEI: Diversity, Equity and

At Booking.com, data drives our decisions. Technology is at our core. And innovation is everywhere. But our company is more than datasets, lines of code or A/B tests. We’re the thrill of the first night in a new place. The excitement of the next morning. The friends you encounter. The journeys you take. The sights you see. And the memories you make. Through our products, partners and people, we make it easier for everyone to experience the world.