Interview guides · Sears

Sears Software Engineer Interview Guide

Sears Software Engineer interview guide: reported rounds, questions and how candidates describe the process.

The 60-second brief

As a Software Engineer at Sears, you are at the heart of maintaining and evolving the digital infrastructure that supports our retail operations. This role is critical to ensuring that our platforms remain robust, scalable, and responsive to the needs of our customers and internal stakeholders. You will contribute to the lifecycle of complex software solutions, balancing immediate technical requirements with long-term system stability. The work environment at Sears is fast-paced and demands a high degree of technical agility. You will often find yourself working across various layers of the stack—from backend service integration to database optimization—to deliver seamless experiences. Whether you are addressing performance bottlenecks or implementing new features, your contributions directly impact the efficiency and reliability of our enterprise-level systems. 02 · Compensation

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

Focus areas

Data Structures & Algorithms (DSA)
Coding Interviews
Java (Core)

The Sears interview process

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

Online Assessment

Initial assessment to evaluate coding skills and technical knowledge.

What to demonstrate

Initial assessment to evaluate coding skills and technical knowledge
Depth in Data Structures & Algorithms (DSA)

How to prepare

Answer aloud and timed: How do you handle multithreading and concurrency in a high-traffic Java environment?
Answer aloud and timed: Can you explain the difference between various SQL joins and when you would use each?

Technical Interviews

In-depth interviews focusing on technical skills and problem-solving abilities.

What to demonstrate

In-depth interviews focusing on technical skills and problem-solving abilities
Depth in Data Structures & Algorithms (DSA)

How to prepare

Answer aloud and timed: What are the primary advantages and potential drawbacks of using Spring Boot for microservices?
Answer aloud and timed: How do you manage exception handling to ensure system stability in production?

Managerial or HR Round

Final interview with management or HR to discuss fit and behavioral scenarios.

What to demonstrate

Final interview with management or HR to discuss fit and behavioral scenarios
Depth in Data Structures & Algorithms (DSA)

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 managerial or hr round above and write down what you would ask to confirm before it.

Where candidates lose points

Think out loud

Interviewers are as interested in your thought process as they are in the final code.

Be honest

If you don't know an answer, say so, but explain how you would go about finding the solution.

Prepare your stories

Use the STAR method (Situation, Task, Action, Result) for behavioral questions to keep your answers structured and impactful.

Review your resume

Be ready to explain any project or technology you have listed in detail.

Questions & practice

How do you handle multithreading and concurrency in a high-traffic Java environment?

Medium · Technical & Core Domain Knowledge

Approach

Say what the runtime actually does before reasoning about the code.
Name what is shared across threads and what owns each piece of state.
Identify the window where an invariant is briefly untrue.
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?

Solve a problem involving binary search or sorting algorithms.

Medium · Coding & Problem Solving

Approach

Restate the input: its shape, its size, and what is guaranteed about it.
Name the brute-force solution and its complexity before improving on it.
Choose the data structure from the access pattern, not from familiarity.
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?

Given an array or stack, how would you optimize a search operation?

Medium · Coding & Problem Solving

Approach

Restate the input: its shape, its size, and what is guaranteed about it.
Name the brute-force solution and its complexity before improving on it.
Choose the data structure from the access pattern, not from familiarity.
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?

Write a function to address a common data structure manipulation task.

Medium · Coding & Problem Solving

Approach

Restate the input: its shape, its size, and what is guaranteed about it.
Name the brute-force solution and its complexity before improving on it.
Choose the data structure from the access pattern, not from familiarity.
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?

Explain the logic behind your chosen approach for a specific algorithmic challenge.

Medium · Coding & Problem Solving

Approach

Restate the input: its shape, its size, and what is guaranteed about it.
Name the brute-force solution and its complexity before improving on it.
Choose the data structure from the access pattern, not from familiarity.
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?

Can you explain the difference between various SQL joins and when you would use each?

Medium · Technical & Core Domain Knowledge

Approach

Name the grain you start from and join outward from it.
Check whether any join is one-to-many before aggregating, or the sums inflate.
Say which index the query would use, and what makes it unusable.
Handle the rows that do not match: that is usually the actual question.

Follow-up

How does the query change if that join becomes one-to-many?
What happens to this when the table is ten times larger?

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

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.
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.
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.
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?

What are the primary advantages and potential drawbacks of using Spring Boot for microservices?

Medium · Technical & Core Domain Knowledge

Approach

Fix the scope first: who calls this, how often, and what they do when it fails.
Name the read and write paths separately; they rarely have the same bottleneck.
Choose a partition key and say what query it makes expensive.
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 do you manage exception handling to ensure system stability in production?

Medium · Technical & Core Domain Knowledge

Approach

Clarify what is being asked and what a complete answer contains.
State your assumptions explicitly before working the problem.
Say what you would check first and why it is the highest-information step.
Work from the requirement backwards to the design.

Follow-up

What assumption would you test first?
How would you know your answer was wrong?

How do you approach debugging a piece of code that is not performing as expected?

Medium · Coding & Problem Solving

Approach

Establish what changed and when, before forming any theory.
Pick a bisection that eliminates candidates whichever way it turns out.
Check the instrumentation before believing the symptom.
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 Sears candidates report.

Day 1 — Map the Sears loop

Write out the reported sequence: Online Assessment, Technical Interviews, Managerial or HR Round.
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 3 reported rounds, with the weakest marked.

Day 2 — Work Data Structures & Algorithms (DSA)

Spend the session on Data Structures & Algorithms (DSA), which Sears candidates report being tested on.
Write one worked example in Data Structures & Algorithms (DSA) and time yourself on it.

Deliverable: One timed worked example in Data Structures & Algorithms (DSA).

Day 3 — Work Coding Interviews

Spend the session on Coding Interviews, which Sears candidates report being tested on.
Write one worked example in Coding Interviews and time yourself on it.

Deliverable: One timed worked example in Coding Interviews.

Day 4 — Work Java (Core)

Spend the session on Java (Core), which Sears candidates report being tested on.
Write one worked example in Java (Core) and time yourself on it.

Deliverable: One timed worked example in Java (Core).

Day 5 — Answer out loud: Technical & Core Domain Knowledge

Answer aloud, timed: How do you handle multithreading and concurrency in a high-traffic Java environment?
Answer aloud, timed: Can you explain the difference between various SQL joins and when you would use each?

Deliverable: Spoken answers to 2 reported Technical & Core Domain Knowledge question(s), under time.

Day 6 — Answer out loud: Coding & Problem Solving

Answer aloud, timed: Solve a problem involving binary search or sorting algorithms.
Answer aloud, timed: Given an array or stack, how would you optimize a search operation?

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

Day 7 — Answer out loud: Behavioral & Situational

Answer aloud, timed: Can you walk us through a project on your resume and describe the specific technical challenges you overcame?
Answer aloud, timed: How do you prioritize tasks when faced with conflicting deadlines?

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.

Describe your experience with Linux command-line tools for troubleshooting performance issues.

Medium · Technical & Core Domain Knowledge

Approach

Pick a story where you made the decision, not one where you watched it.
State the situation in two sentences and spend the rest on the reasoning.
Give the blast radius: what could have broken, and what you measured.
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?