Design a financial reconciliation pipeline
PremiumData pipelineHard
- Reconciliation
- Matching rules
- Double entry ledger
Quick answer
This data pipeline interview question asks you to design a financial reconciliation pipeline. Aim for a design that moves data from sources to consumers reliably and on time, then explain ingestion, processing, storage and trade-offs. Interviewers want to see how you handle volume, late or bad data and failures along the way.
The problem
Design a financial reconciliation pipeline for a payments company: every day it matches 40 million internal ledger entries against settlement files from 25 banks and 6 card processors and flags every difference for finance. The hard parts are many-to-one matches, settlement delays and fees, late or corrected files, and results auditors trust.
If the ledger says a merchant was paid but the bank never sent the money, someone must know by morning. Reconciliation is how the company proves its books match reality.
What must a financial reconciliation pipeline do?
- Match: Match ledger entries to external records one-to-one, many-to-one (a batched payout) and one-to-many (a split settlement).
- Exceptions: Put every unmatched or mismatched item in a queue with a reason, owner and age, and let analysts resolve it with a note.
How well must it do it?
- Correctness: No auto-match may hide a real difference; every match records the rule and inputs behind it.
- Deadline: All files arrive by 06:00; the report is ready by 09:00.
What scale should you design for?
Use these numbers in your estimates.
The scale numbers unlock with this questionUnlock
Key concepts
- Reconciliation
- Matching rules
- Double entry ledger
- Settlement files
- Exception queues
- Idempotent batch jobs
How you’ll practise
- Requirements
- Data volume
- Ingestion
- Storage and processing
- Serving and freshness
- Wrap-up
Lala, personalized to you, gives a hint when you ask and reviews your design when you are ready.
What do interviewers look for?
In any data pipeline design round.
- Clarifies sources, consumers and freshness needs
- Chooses batch, streaming or both with reasons
- Handles late, duplicate and malformed records
- Makes each stage safe to retry
- Explains storage formats and partitioning
- Plans monitoring, backfills and data quality checks
Questions people ask about this interview question
- Which design type is this question?
- It is a data pipeline question. You design a financial reconciliation pipeline and explain your choices the way you would in an interview.
- Is this question asked at entry level?
- It is marked Hard. It suits engineers preparing for senior interviews, where you are expected to drive the discussion and go deep on trade-offs.
- What should I cover first?
- Start with the data sources, the consumers and how fresh the data must be. Agree on scope with the interviewer before you design anything.
- Can I practise it for free?
- It is a premium question. Sign up and unlock it once for 10 credits; it then stays unlocked. When you finish, Lala, your personalized AI mentor, can review your design for 30 credits.
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Updated · Written by the SevyDevy team