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Egen Software Engineer Interview Guide

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

The 60-second brief

As a Software Engineer at Egen, you are a critical driver of the company’s ability to deliver high-impact digital solutions. You will work at the intersection of complex problem-solving and modern technology stacks, contributing to projects that often involve data-intensive applications, cloud infrastructure, and scalable web architectures. Your role is not just about writing code; it is about architecting robust solutions that solve real-world business challenges for clients. The environment at Egen is dynamic and fast-paced. You will be expected to collaborate with cross-functional teams, including product managers, architects, and designers, to translate ambiguous requirements into technical reality.

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

Focus areas

  • Java
  • OOP Concepts (Object-Oriented Programming)
  • REST APIs

The Egen interview process

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

Recruiter Screening

Initial contact with a recruiter to assess your background and fit for the role.

What to demonstrate

  • Initial contact with a recruiter to assess your background and fit for the role
  • Depth in Java

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

Includes online coding challenges or take-home projects to evaluate technical skills.

What to demonstrate

  • Includes online coding challenges or take-home projects to evaluate technical skills
  • Depth in Java

How to prepare

  • Answer aloud and timed: Is Java pass-by-value or pass-by-reference?
  • Answer aloud and timed: What are the core pillars of OOP (abstraction, inheritance, polymorphism, encapsulation)?

Video Interviews

Interviews conducted via video with senior engineers or technical directors to assess coding capabilities.

What to demonstrate

  • Interviews conducted via video with senior engineers or technical directors to assess coding capabilities
  • Depth in Java

How to prepare

  • Answer aloud and timed: How do you handle deadlocks in a multi-threaded environment?
  • Answer aloud and timed: What are the key differences between DELETE and TRUNCATE in database management?

Where candidates lose points

Own your resume

Be prepared to explain every technology and project listed on your CV in extreme detail. If you haven't used a technology recently, be honest about your familiarity level.

Be ready for the "rapid-fire" round

Some interviewers use this style to test how you handle pressure. Stay calm, answer concisely, and don't be afraid to ask for a moment to think if the question is complex.

Practice live coding

Since many interviews involve screen sharing and IDE work, practice writing code while explaining your thought process out loud.

Research the company culture

Egen values consultants who are professional, communicative, and reliable. Demonstrating these soft skills is just as important as your technical score.

Questions & practice

Is Java pass-by-value or pass-by-reference?

Medium · Core Java & Object-Oriented Programming

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 a time you had to optimize a piece of code that was performing poorly.

Medium · Problem Solving & System Logic

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?

Describe a complex technical challenge you faced in a previous project and your specific contribution to the s

Medium · Problem Solving & System Logic

Describe a complex technical challenge you faced in a previous project and your specific contribution to the solution.

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?

Find version gaps and relay lag with window functions

Medium · window functions · event tables · frame semantics

outbox_event holds event_id, aggregate_type, aggregate_id, aggregate_version, event_type, payload, status ('pending','published','dead'), attempts, created_at, published_at. A projection is missing rows and you must decide whether the relay skipped events or the consumer dropped them. Write three queries over the last seven days: one listing every aggregate_id whose published aggregate_version sequence has a hole, one giving per-day counts with a running total, and one returning the newest published event per aggregate. For each, say where the window function is evaluated relative to WHERE and LIMIT. PostgreSQL 16.

Approach

  1. Gaps: compute lead(aggregate_version) OVER (PARTITION BY aggregate_id ORDER BY aggregate_version) in a subquery, then filter next_version <> aggregate_version + 1 in the outer query. Window functions are evaluated after WHERE, GROUP BY and HAVING and before the outer ORDER BY and LIMIT, so the predicate cannot sit in the same WHERE clause and PostgreSQL 16 has no QUALIFY.
  2. Say what the seven-day filter does to the answer: it truncates every partition, so the first row per aggregate has no predecessor inside the window and a hole spanning the boundary is invisible. Widen the window, or join to resource.version as the authority for the true maximum.
  3. Running total: SELECT date_trunc('day', created_at) AS d, count() AS n, sum(count()) OVER (ORDER BY date_trunc('day', created_at) ROWS UNBOUNDED PRECEDING). An aggregate inside a window call is legal because grouping runs before windowing. The grouping key is unique per row here so ROWS and RANGE agree, but write the frame anyway — over ungrouped rows with tied timestamps the default RANGE frame pulls in every peer row and the total jumps.
  4. Newest per aggregate: DISTINCT ON (aggregate_id) ... ORDER BY aggregate_id, aggregate_version DESC is the cheap PostgreSQL-only form when an index matches that order; row_number() OVER (PARTITION BY aggregate_id ORDER BY aggregate_version DESC) = 1 is the portable form and needs a subquery for the same evaluation-order reason as the gap query.

Follow-up

  • Relay failover redelivers events. Does a duplicate break the gap query, and how would you detect one from this table alone?
  • Turn the gap check into a continuous monitor rather than a query someone runs after an incident. What does it watch?

Keep soft-deleted accounts from blocking re-registration

Easy · soft delete · unique constraints · engine differences

app_user holds user_id, tenant_id, email CITEXT, password_hash (NULL for SSO principals), email_verified_at, auth_version, status ('invited','active','suspended','deactivated'), created_at, updated_at, deleted_at. Two live accounts for one address inside a tenant must be impossible, but an address freed by a soft delete must be reusable, and the same tenant may delete and re-register it repeatedly. Write the uniqueness DDL for PostgreSQL 16, then the equivalent for MySQL 8 where partial indexes do not exist, and say what each permits once three deleted rows already hold that address.

Approach

  1. Start from what is actually unique: not (tenant_id, email), but (tenant_id, email) among live rows. PostgreSQL says that directly — CREATE UNIQUE INDEX app_user_live_email ON app_user (tenant_id, email) WHERE deleted_at IS NULL. A full constraint over the same two columns burns the address permanently the first time someone deletes an account.
  2. Keep case-insensitivity in the type or the index, never in the application: CITEXT as given, or UNIQUE (tenant_id, lower(email)) as an expression index where the extension is unavailable. A case-sensitive unique column is exactly how two accounts for one human appear.
  3. For MySQL 8 the predicate has to move inside the key: add a discriminator column that is a constant 0 while the row is live and is set to user_id on delete, with UNIQUE (tenant_id, email, deleted_marker). Live rows share the constant and still collide; deleted rows differ from each other and stop colliding.
  4. State the NULL variant and its dependency: leaving the marker NULL for deleted rows also works, because a unique index treats NULLs as distinct — true in MySQL, and true in PostgreSQL only under the default NULLS DISTINCT, which PostgreSQL 15 lets you reverse. Check the polarity against the three existing deleted rows: constant-on-live is what preserves the collision you want, and reversing it silently admits duplicate live accounts.

Follow-up

  • A deleted account re-registers with the same address the next day. Do the old resource rows follow the new user_id, and how does the API keep the two principals apart?
  • How do you honour an erasure request while resource_revision.actor_user_id still references this table?

What is the difference between Hashtable and HashMap?

Medium · Core Java & Object-Oriented Programming

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. 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 final, finally, and finalize differ in Java?

Medium · Core Java & Object-Oriented Programming

Approach

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

Follow-up

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

What are the core pillars of OOP (abstraction, inheritance, polymorphism, encapsulation)?

Medium · Core Java & Object-Oriented Programming

Approach

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

Follow-up

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

What are the key differences between DELETE and TRUNCATE in database management?

Medium · Web Technologies & Frameworks

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. 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 does AngularJS or React state management work in your projects?

Medium · Web Technologies & Frameworks

Approach

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

Follow-up

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

Can you explain the lifecycle of a RESTful web service?

Medium · Web Technologies & Frameworks

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. 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 optimize CSS3 and HTML5 for performance?

Medium · Web Technologies & Frameworks

Approach

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

Follow-up

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

What are the advantages of using Spring Boot for microservices?

Medium · Web Technologies & Frameworks

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 design a scalable API for a high-traffic application?

Medium · Problem Solving & System Logic

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 do you approach debugging a system when the root cause is unclear?

Medium · Problem Solving & System Logic

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 Egen candidates report.

Day 1 — Map the Egen loop

  • Write out the reported sequence: Recruiter Screening, Technical Assessments, Video Interviews.
  • 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 Java

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

Deliverable: One timed worked example in Java.

Day 3 — Work OOP Concepts (Object-Oriented Programming)

  • Spend the session on OOP Concepts (Object-Oriented Programming), which Egen candidates report being tested on.
  • Write one worked example in OOP Concepts (Object-Oriented Programming) and time yourself on it.

Deliverable: One timed worked example in OOP Concepts (Object-Oriented Programming).

Day 4 — Work REST APIs

  • Spend the session on REST APIs, which Egen candidates report being tested on.
  • Write one worked example in REST APIs and time yourself on it.

Deliverable: One timed worked example in REST APIs.

Day 5 — Answer out loud: Core Java & Object-Oriented Programming

  • Answer aloud, timed: What is the difference between Hashtable and HashMap?
  • Answer aloud, timed: How do final, finally, and finalize differ in Java?

Deliverable: Spoken answers to 2 reported Core Java & Object-Oriented Programming question(s), under time.

Day 6 — Answer out loud: Web Technologies & Frameworks

  • Answer aloud, timed: What are the key differences between DELETE and TRUNCATE in database management?
  • Answer aloud, timed: How does AngularJS or React state management work in your projects?

Deliverable: Spoken answers to 2 reported Web Technologies & Frameworks question(s), under time.

Day 7 — Answer out loud: Problem Solving & System Logic

  • Answer aloud, timed: Explain a time you had to optimize a piece of code that was performing poorly.
  • Answer aloud, timed: How would you design a scalable API for a high-traffic application?

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

Behavioural preparation

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

How do you handle deadlocks in a multi-threaded environment?

Medium · Core Java & Object-Oriented Programming

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?

Argue against a design, lose, and commit anyway

Medium · disagreement · service boundaries · decision records

Describe a design you argued against and lost. State the failure you predicted as a named mechanism, not a feeling about complexity: two services that would need one transaction, a projection with no rebuild path, a write path with no idempotency key. Say what evidence you brought, what the decision maker weighed instead, and what you did after the decision was made: what you instrumented, what you wrote down, and whether the prediction came true. Five minutes.

Approach

  1. State the prediction in falsifiable form up front: the mechanism, the condition that triggers it, and the observable outcome. A prediction that cannot be checked also cannot be credited to you later.
  2. Show the evidence you had at the time and label each piece honestly as measured, analogous, or intuition. Keeping the intuition is fine; disguising it as data is the thing that erodes your standing in the next argument.
  3. Represent the opposing case at full strength, including the constraint you did not control: a fixed date, a team boundary, or the fact that the decision was cheap to reverse and yours was not.
  4. Make disagree-and-commit concrete. Name the artefact you left behind so the prediction could be settled without you: the alert and its threshold, the counter on the dashboard, the decision note that recorded the trade-off and the condition that would revisit it.

Follow-up

  • What threshold on that alert would have proved you right, and did anyone ever look at it?
  • If the same proposal arrived tomorrow with the same deadline, would you argue it the same way?

Tell callers you do not own that their integration breaks

Medium · deprecation · compatibility · stakeholders

A field in a write endpoint's response must change shape. You own the endpoint; you do not own the four internal callers or the outbound webhook consumers who read it. Describe a deprecation you were responsible for: what you shipped first, how you established who was actually reading the field, the window you gave and what set its length, what you did about the consumer who never moved, and how you decided removal was safe. Name the signal you used, not the announcement you sent.

Approach

  1. Establish the reader set empirically rather than from a wiki of owners: per-field usage counters keyed by principal, or access logs attributed to a consumer. State the blind spot of whichever you pick, since a consumer that reads the field only on a monthly job will not appear in a week of logs.
  2. Ship additive first. Populate the new field alongside the old one so no reader is forced to move, which is also what keeps a rolling deploy safe, because old and new instances answer the same requests at the same time and a rollback must still find the old shape present.
  3. Set the window from the slowest legitimate consumer's release cadence, not from your calendar, and decide separately what to do for a consumer with no release process at all, such as an external webhook endpoint you can only email.
  4. Convert silence into evidence before you rely on it: a short, low-traffic removal window that makes a still-dependent consumer fail visibly and loudly while you are watching, rather than at three in the morning after you have moved on.

Follow-up

  • How would you detect a consumer that reads the field only during a monthly export?
  • One caller refuses to move and has a commercial relationship behind it. What changes in your plan and what does not?