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Design

Design a Real-Time Order Pipeline for a Fintech Payments Platform

FreeVerified credential3 weeksAdvanced

Overview

What this challenge is about.

You receive a synthetic Kafka stream of around 500 transactions per second, a static merchant dimension table (about 80,000 rows), and a daily FX rate snapshot. Design an end-to-end streaming pipeline using Kafka plus a stream-processing layer (Flink, Spark Structured Streaming, or Kafka Streams), with the enriched output landing in a columnar store (BigQuery, Snowflake, or ClickHouse). Success is end-to-end latency under five minutes at p95 (95th-percentile, meaning 95 of every 100 transactions arrive within that bound), an at-least-once delivery guarantee with documented deduplication, and a monthly cost projection for ten times today's volume.

CredentialBlockchain-anchored
ShareableLinkedIn-ready
LanguageEnglish
PaceSelf-paced

The Brief

What you'll do, and what you'll demonstrate.

Replace the nightly batch reporting flow with a streaming pipeline that delivers enriched transactions to analytics in under five minutes at p95.

Earning criteria — what you'll demonstrate

  • Design a streaming pipeline with explicit latency and delivery guarantees
  • Trade off stream-processing engines on cost, complexity, and team familiarity
  • Model an enrichment join between a hot stream and a static dimension
  • Estimate cloud cost at multiple traffic scales

Program Fit

Where this fits in your program.

Sharpens the same skills your degree expects you to demonstrate.

Skills

Skills you'll demonstrate.

Each one shows up on your verified credential.

Careers

Roles this prepares you for.

Real titles. Real skill bridges. Pick the one closest to your trajectory.

Data Engineer

Designing a streaming pipeline against real latency and cost budgets is exactly the first month of work for a junior data engineer at any payments or analytics company.

This challenge sharpens

  • streaming-data
  • kafka
  • stream-processing

MLOps Engineer

The same streaming primitives feed online fraud and recommendation models; MLOps engineers own this layer end-to-end at fintechs.

This challenge sharpens

  • streaming-data
  • system-design
  • stream-processing

AI Solutions Architect

Writing a costed, tradeoff-justified architecture memo for a head-of-data is the bread and butter of a solutions architect role.

This challenge sharpens

  • system-design
  • cost-modeling
  • data-modeling

One more thing

You can put a credential on your CV by Friday.