Senior Data Engineer - FinTech

Delivery Hero — Germany · Posted ~2 hours ago

Senior Full-time Visa History ✓

Skills

Data engineering Apache Flink Streaming data pipelines Batch pipelines Data historization Data quality Observability Fraud prevention Data architecture Python SQL Cross-functional collaboration Streaming data

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Summary ✨ AI‑Generated

A global technology organization is looking for a senior data engineer to strengthen the data foundation supporting financial risk and fraud prevention. You will develop streaming and batch pipelines, historization, data quality and observability capabilities, while making data reliable for rule evaluation, model development, inference and backtesting. You will own solutions from architecture and development through operations.

Highlights

Build critical data infrastructure for fraud prevention, own solutions across their full lifecycle, work closely with data science and engineering teams, and tackle large-scale real-time and historical data challenges.

Description

Job DescriptionWe are on the lookout for a Senior Data Engineer (Fintech) to help build the next-generation data foundation for fraud prevention. Be part of building the financial backbone of Delivery Hero. You’ll develop products that empower millions of customers and merchants, from seamless payments to innovative financial solutions like wallets and credit. Your work will support our path to profitability by creating financial flexibility for users and enabling smooth transactions across our markets. Our Flink-based streaming platform already powers real-time fraud signals. In this role, you will build and enhance historization capabilities, batch pipelines, data quality framework, and observability tooling to make fraud data reliable, traceable, and easy to use for rule evaluation, model training, inference, and backtesting. You will work closely with Data Science and Engineering teams and own the full lifecycle of these data solutions, from design and development to operation and continuous improvement. Build accurate, point-in-time-correct datasets for model training, backtesting, and analysis. Design and build scalable batch pipelines that complement our existing Flink-based streaming platform. Develop robust controls for data completeness, freshness, anomaly detection, reconciliation, and business-logic accuracy. Build observability capabilities that surface pipeline failures, data drift, and quality issues before they affect downstream models or fraud rules. Partner with Data Scientists and Fraud Ops to translate fraud-prevention use cases into scalable, resilient data products while maintaining consistency between batch and real-time processing.