Build a Real-Time Streaming Pipeline for Card-Fraud Scoring
Overview
What this challenge is about.
Build a Real-Time Streaming Pipeline for Card-Fraud Scoring. Advanced challenge in code. Writing production code that solves real engineering problems, earn ...
The Brief
What you'll do, and what you'll demonstrate.
Build a Kafka-based streaming pipeline that enriches card transactions with rolling cardholder features, scores them with the provided model, and stays under 500ms 95th-percentile end-to-end latency at peak load.
This is not a coding exercise. It is the work a software engineer does between a Jira ticket and a merged PR. That distinction matters to every hiring manager who has seen candidates solve LeetCode problems and none who have shipped production code under real constraints.
When you finish, you will have something most graduates do not: a real-world deliverable, verified by Ewance, that you can show to a hiring manager and say "I did this. Here is the proof."
Earning criteria — what you'll demonstrate
- Design a stateful stream-processing topology with correct event-time semantics, watermarks, and late-data handling
- Compute multi-horizon rolling-window features (1h/24h/7d) per key as a low-latency enrichment step
- Integrate an external scoring service as an inline enrichment without breaking the latency budget
- Measure and defend end-to-end latency and throughput under a realistic, bursty load profile
- Communicate a streaming architecture clearly to a non-implementing risk stakeholder
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Aligned coursework coming soon.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Stream Processing
Apply stream processing to solve real industry problems and demonstrate production-level capability.
- Kafka
Apply kafka to solve real industry problems and demonstrate production-level capability.
- Flink
Apply flink to solve real industry problems and demonstrate production-level capability.
- Feature Engineering
Apply feature engineering to solve real industry problems and demonstrate production-level capability.
- Benchmarking
Apply benchmarking to solve real industry problems and demonstrate production-level capability.
- Java
Apply java to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
Streaming Data / Real-Time Backend Engineer
Builds production stream-processing systems where correctness under event-time and tight latency both matter. This challenge mirrors that work end to end: designing a stateful topology, holding a strict latency budget, and proving it under realistic load.
This challenge sharpens
- stream-processing
- kafka
- flink
Fraud / Risk Platform Engineer
Engineers the low-latency scoring and feature pipelines that fraud models depend on in banking. Here you wire rolling behavioral features into a live scoring path, the core daily task of a risk-platform engineer.
This challenge sharpens
- feature-engineering
- stream-processing
- kafka
Performance / Backend Reliability Engineer
Owns latency and throughput targets for high-volume services and proves them empirically. The benchmarking and percentile-defense work in this challenge maps directly onto that responsibility.
This challenge sharpens
- benchmarking
- stream-processing
- java