FreeChargeBiz Software Engineer Interview Guide

The 60-second brief

As a Software Engineer at FreeChargeBiz, you are at the heart of our mission to simplify digital transactions for merchants and businesses. You will build, scale, and maintain the robust backend services and intuitive interfaces that form the backbone of our payment processing ecosystem. Your work directly impacts how thousands of businesses handle revenue, manage customer data, and navigate complex financial workflows. This role is critical because the FreeChargeBiz platform operates at significant scale, requiring engineers who can balance high-performance requirements with the absolute necessity for security and transaction integrity. You won’t just be writing code; you will be solving real-world problems involving distributed systems, database optimization, and API reliability.

This guide is scoped to a Software Engineer candidate at FreeChargeBiz.

Focus areas

• Software Engineering Fundamentals
• Programming Problem Solving
• Data Structures

The FreeChargeBiz interview process

FreeChargeBiz candidates report 4 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

Initial Screening

Candidates undergo an initial screening to assess their fit for the SDE1 position.

What to demonstrate

• Candidates undergo an initial screening to assess their fit for the SDE1 position
• Depth in Software Engineering Fundamentals

How to prepare

• Be able to walk your CV end to end in two minutes, and say why this company specifically.
• Have your salary expectations, notice period and location constraints ready, and ask for the rest of the loop in writing.

Technical Assessments

Candidates participate in a series of technical assessments to evaluate their coding fundamentals.

What to demonstrate

• Candidates participate in a series of technical assessments to evaluate their coding fundamentals
• Depth in Software Engineering Fundamentals

How to prepare

• Answer aloud and timed: How would you handle a race condition in a multi-threaded service?
• Answer aloud and timed: Given a stream of transaction events, how do you efficiently calculate running totals?

Architectural Discussions

Deeper architectural discussions take place to assess candidates' design and problem-solving skills.

What to demonstrate

• Deeper architectural discussions take place to assess candidates' design and problem-solving skills
• Depth in Software Engineering Fundamentals

How to prepare

• Answer aloud and timed: Discuss the time complexity of your solution for filtering merchant records.
• Answer aloud and timed: Design a rate-limiting service for our public-facing APIs.

Behavioral Evaluations

Candidates are evaluated on behavioral aspects to determine cultural fit and potential for growth.

What to demonstrate

• Candidates are evaluated on behavioral aspects to determine cultural fit and potential for growth
• Depth in Software Engineering Fundamentals

How to prepare

• Prepare three examples from your own work, each with a decision you made and an outcome you can quantify.
• Re-read the description of the behavioral evaluations above and write down what you would ask to confirm before it.

Where candidates lose points

Think Out Loud

Your interviewer wants to hear your thought process. Even if you are stuck, explain what you are considering; this helps the interviewer guide you.

Be Honest About Your Limits

If you don't know a specific technology, explain how you would go about learning it or how it relates to concepts you do understand.

Focus on Trade-offs

In system design, there is rarely one "right" answer. Always discuss the trade-offs (e.g., latency vs. consistency) of your proposed solution.

Before your interview, spend time reviewing the FreeChargeBiz product suite

Understanding the user's perspective will give you a significant advantage in design rounds.

Questions & practice

Implement a function to optimize transaction logging in a high-concurrency environment.

Medium · Technical & Coding Fundamentals

Approach

1. Say what the runtime actually does before reasoning about the code.
2. Name what is shared across threads and what owns each piece of state.
3. Identify the window where an invariant is briefly untrue.
4. Distinguish a value from a reference to it, and say which one you handed out.

Follow-up

• What happens if two callers reach this at the same time?
• Where could this allocate more than you expect?

Explain the trade-offs between using a relational database versus a NoSQL store for payment metadata.

Medium · Technical & Coding Fundamentals

Approach

1. Restate the input: its shape, its size, and what is guaranteed about it.
2. Name the brute-force solution and its complexity before improving on it.
3. Choose the data structure from the access pattern, not from familiarity.
4. State the target complexity and say which constraint rules the naive version out.

Follow-up

• How does this change if the input no longer fits in memory?
• What is the worst case, and how likely is it on real data?

How would you handle a race condition in a multi-threaded service?

Medium · Technical & Coding Fundamentals

Approach

1. Say what the runtime actually does before reasoning about the code.
2. Name what is shared across threads and what owns each piece of state.
3. Identify the window where an invariant is briefly untrue.
4. Distinguish a value from a reference to it, and say which one you handed out.

Follow-up

• What happens if two callers reach this at the same time?
• Where could this allocate more than you expect?

Given a stream of transaction events, how do you efficiently calculate running totals?

Medium · Technical & Coding Fundamentals

Approach

1. Restate the input: its shape, its size, and what is guaranteed about it.
2. Name the brute-force solution and its complexity before improving on it.
3. Choose the data structure from the access pattern, not from familiarity.
4. State the target complexity and say which constraint rules the naive version out.

Follow-up

• How does this change if the input no longer fits in memory?
• What is the worst case, and how likely is it on real data?

Discuss the time complexity of your solution for filtering merchant records.

Medium · Technical & Coding Fundamentals

Approach

1. Restate the input: its shape, its size, and what is guaranteed about it.
2. Name the brute-force solution and its complexity before improving on it.
3. Choose the data structure from the access pattern, not from familiarity.
4. State the target complexity and say which constraint rules the naive version out.

Follow-up

• How does this change if the input no longer fits in memory?
• What is the worst case, and how likely is it on real data?

Stop tag and share joins from fanning out a page

Medium · join fan-out · semi-joins · many-to-many

resource_tag is (resource_id, tag_id) with PK (resource_id, tag_id); resource_share is (resource_id, shared_with_user_id, permission). The tagged-and-shared listing inner-joins resource to both, filters tenant_id, tag_id = ANY($2) and shared_with_user_id = $3, orders by updated_at DESC and takes 50. Pages come back with fewer than 50 distinct resources and the total in the header is far too high. Explain the row multiplication, rewrite both the page query and the count query so each is correct, and name the index each one needs. PostgreSQL 16.

Approach

1. Do the arithmetic against the predicates that are actually there. An inner join emits one row per matching child row, and both joins are filtered: tag_id = ANY($2) admits only the requested tags, shared_with_user_id = $3 admits one user's share rows. So a resource holding three of the requested tags and shared with $3 once yields three rows, not one — the multiplier is its count of matching tags times its share rows for that single user, and that second factor is 1 unless the table admits duplicate (resource_id, shared_with_user_id) pairs. LIMIT 50 then limits rows rather than resources, and COUNT(*) counts pairs — the header is the product, not the population.
2. Reject DISTINCT as the fix. It deduplicates after the product has been built, so the planner must materialise and sort the fanned-out set before the LIMIT can apply, and it leaves any SUM or AVG in the same select list wrong.
3. Rewrite both filters as semi-joins, keeping resource as the only row source: AND EXISTS (SELECT 1 FROM resource_tag rt WHERE rt.resource_id = r.resource_id AND rt.tag_id = ANY($2)) and the same shape against resource_share. A semi-join stops at the first match per resource and preserves the driving index order, so ORDER BY updated_at DESC, resource_id DESC LIMIT 50 still stops after 50 rows.
4. Count with the same predicates and no join at all: SELECT count(*) FROM resource r WHERE r.tenant_id = $1 AND r.status = 'active' AND EXISTS (...) AND EXISTS (...). Nothing multiplies a resource, so the number is the population.

Follow-up

• The filter changes from 'any of these tags' to 'all of these tags'. Rewrite it and state what it costs relative to the ANY form.
• A resource can be shared with the same user twice under different permissions. Does your count change, and should it?

Denormalise tenant onto revisions and backfill it live

Hard · denormalisation · online migration · backfill

resource_revision (revision_id, resource_id, version, actor_user_id, change_kind, patch, request_id, created_at) has 400M rows and no tenant column; tenant_id lives only on resource. Two reads need it: a tenant-scoped audit feed ordered by created_at DESC, and an offboarding purge. Both join back to resource today. Justify adding tenant_id to resource_revision against those two reads, name the anomaly the copy introduces and the constraint that prevents it, then give the ordered migration for a live table taking 1.2k writes/second — the lock each step takes, how the backfill is batched, and where each step stops being reversible. PostgreSQL 16.

Approach

1. Justify from the access path rather than from taste. Without the column, the audit feed either scans resource_revision by created_at and discards other tenants' rows, or resolves the tenant's resource_ids first and probes with them — both proportional to the tenant's whole history rather than to one page. With (tenant_id, created_at DESC, revision_id DESC) it is a seek that stops at 50 rows, and the purge becomes a ranged delete instead of a join.
2. Name the cost exactly: a second copy of a fact can disagree with the first. Make the disagreement unwritable rather than documented — add UNIQUE (resource_id, tenant_id) on resource so it can serve as a foreign-key target, then FOREIGN KEY (resource_id, tenant_id) REFERENCES resource (resource_id, tenant_id) on the revision table. A revision can then only ever carry its parent's tenant.
3. Step one, expand: ALTER TABLE resource_revision ADD COLUMN tenant_id BIGINT NULL, with no default, so it is a catalogue change and no rewrite. It still needs ACCESS EXCLUSIVE for an instant, and that instant queues behind the longest open transaction on the table while every later query queues behind it — set lock_timeout to 2s and retry rather than wait.
4. Step two, dual-write: deploy the writer that populates tenant_id on every new revision while reads still use the join. Reversible by redeploying the previous build, because nothing reads the column yet.

Follow-up

• The backfill is half finished and a rollback is required. What state is the table in, and what does the previous build do with a half-populated column?
• How do you verify the backfill actually finished, given rows are still being inserted while it runs?

Design a rate-limiting service for our public-facing APIs.

Medium · System Design & Architecture

Approach

1. Fix the scope first: who calls this, how often, and what they do when it fails.
2. Name the read and write paths separately; they rarely have the same bottleneck.
3. Choose a partition key and say what query it makes expensive.
4. State the consistency you need, and where you are willing to be stale.

Follow-up

• What breaks first when traffic grows ten times?
• How does this behave when that dependency is down for an hour?

How would you architect a notification system that sends alerts to merchants across multiple channels?

Medium · System Design & Architecture

Approach

1. Fix the scope first: who calls this, how often, and what they do when it fails.
2. Name the read and write paths separately; they rarely have the same bottleneck.
3. Choose a partition key and say what query it makes expensive.
4. State the consistency you need, and where you are willing to be stale.

Follow-up

• What breaks first when traffic grows ten times?
• How does this behave when that dependency is down for an hour?

What strategies would you employ to ensure high availability for a payment gateway?

Medium · System Design & Architecture

Approach

1. Fix the scope first: who calls this, how often, and what they do when it fails.
2. Name the read and write paths separately; they rarely have the same bottleneck.
3. Choose a partition key and say what query it makes expensive.
4. State the consistency you need, and where you are willing to be stale.

Follow-up

• What breaks first when traffic grows ten times?
• How does this behave when that dependency is down for an hour?

Explain how you would design a database schema for a multi-tenant merchant platform.

Medium · System Design & Architecture

Approach

1. Fix the scope first: who calls this, how often, and what they do when it fails.
2. Name the read and write paths separately; they rarely have the same bottleneck.
3. Choose a partition key and say what query it makes expensive.
4. State the consistency you need, and where you are willing to be stale.

Follow-up

• What breaks first when traffic grows ten times?
• How does this behave when that dependency is down for an hour?

Describe a time you faced a production issue; how did you debug and resolve it?

Medium · Behavioral & Situational

Approach

1. Establish what changed and when, before forming any theory.
2. Pick a bisection that eliminates candidates whichever way it turns out.
3. Check the instrumentation before believing the symptom.
4. Separate the trigger from the cause; the deploy is rarely the bug.

Follow-up

• What would you look at first, and what would it rule out?
• How would you tell a cause from a coincidence here?

Suggested practice checklist

Built from the rounds and topics FreeChargeBiz candidates report.

Day 1 — Map the FreeChargeBiz loop

• Write out the reported sequence: Initial Screening, Technical Assessments, Architectural Discussions, Behavioral Evaluations.
• For each round, write one sentence on what it is judging, from the description above, and mark the one you are least ready for.

Deliverable: A one-page map of the 4 reported rounds, with the weakest marked.

Day 2 — Work Software Engineering Fundamentals

• Spend the session on Software Engineering Fundamentals, which FreeChargeBiz candidates report being tested on.
• Write one worked example in Software Engineering Fundamentals and time yourself on it.

Deliverable: One timed worked example in Software Engineering Fundamentals.

Day 3 — Work Programming Problem Solving

• Spend the session on Programming Problem Solving, which FreeChargeBiz candidates report being tested on.
• Write one worked example in Programming Problem Solving and time yourself on it.

Deliverable: One timed worked example in Programming Problem Solving.

Day 4 — Work Data Structures

• Spend the session on Data Structures, which FreeChargeBiz candidates report being tested on.
• Write one worked example in Data Structures and time yourself on it.

Deliverable: One timed worked example in Data Structures.

Day 5 — Answer out loud: Technical & Coding Fundamentals

• Answer aloud, timed: Implement a function to optimize transaction logging in a high-concurrency environment.
• Answer aloud, timed: Explain the trade-offs between using a relational database versus a NoSQL store for payment metadata.

Deliverable: Spoken answers to 2 reported Technical & Coding Fundamentals question(s), under time.

Day 6 — Answer out loud: System Design & Architecture

• Answer aloud, timed: Design a rate-limiting service for our public-facing APIs.
• Answer aloud, timed: How would you architect a notification system that sends alerts to merchants across multiple channels?

Deliverable: Spoken answers to 2 reported System Design & Architecture question(s), under time.

Day 7 — Answer out loud: Behavioral & Situational

• Answer aloud, timed: Describe a time you faced a production issue; how did you debug and resolve it?
• Answer aloud, timed: How do you handle feedback from senior engineers on your code reviews?

Deliverable: Spoken answers to 2 reported Behavioral & Situational question(s), under time.

Behavioural preparation

Behavioural rounds judge the decision you made and what it cost.

How do you handle feedback from senior engineers on your code reviews?

Medium · Behavioral & Situational

Approach

1. Pick a story where you made the decision, not one where you watched it.
2. State the situation in two sentences and spend the rest on the reasoning.
3. Give the blast radius: what could have broken, and what you measured.
4. Name the disagreement and how you resolved it with evidence.

Follow-up

• What would you do differently if you ran that again?
• How did you know your change caused the improvement?

Tell us about a technical project where you had to pivot due to changing requirements.

Medium · Behavioral & Situational

Approach

1. Pick a story where you made the decision, not one where you watched it.
2. State the situation in two sentences and spend the rest on the reasoning.
3. Give the blast radius: what could have broken, and what you measured.
4. Name the disagreement and how you resolved it with evidence.

Follow-up

• What would you do differently if you ran that again?
• How did you know your change caused the improvement?

Reverse your own decision and price the reversal

Medium · reversibility · measurement · migrations

Describe a technical decision you made and later reversed. Pick one that cost something: a service you split and merged back, a cache you added and removed, an index you created that pushed the planner onto a worse plan, a projection you rebuilt from scratch. State what you believed when you decided, the measurement that changed your mind, how long the wrong version ran in production, and what the reversal cost in migrations, dual writes, and a deprecation window for callers you did not own.

Approach

1. State the original rationale without irony, in the version you would still defend given what was known then. If it is not defensible, the story is about carelessness rather than judgement, and a different example serves you better.
2. Give the measurement that moved with a before and after: the p99 that did not improve, the cache hit rate that sat at 40%, the plan that flipped to a sequential scan once the table passed a size you can name.
3. Cost the reversal in steps, not adjectives: expand-and-contract deploys, the dual-write window, the callers who had to be notified, the rows already written in the wrong shape that had to be backfilled or abandoned.
4. Distinguish reversal from rewrite by naming what you kept. Most good reversals preserve the schema or the interface and undo one decision inside it, which is also why they were affordable.

Follow-up

• What in that decision was irreversible, and did you know it was irreversible when you made it?
• How did you tell the people who had already built on top of the original decision?