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Echo Global Logistics Software Engineer Interview Guide

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

The 60-second brief

A Software Engineer at Echo Global Logistics plays a pivotal role in developing and maintaining software solutions that streamline logistics and transportation processes. This position is essential for ensuring that the company's technology infrastructure supports its mission of providing efficient and reliable logistics services. As a Software Engineer, you will work on innovative projects that directly impact client satisfaction and operational efficiency, making your contributions critical to the company's success. In this role, you will engage with various teams, including product management and operations, to create software that enhances user experiences and optimizes supply chain management. Projects may involve developing applications for real-time tracking, data analysis, or automation, providing a unique opportunity to work on complex problems in a fast-paced environment.

This guide is scoped to a Software Engineer candidate at Echo Global Logistics.

Focus areas

Problem Solving
Angular (Frontend Framework)
Database Concepts (SQL Joins)

The Echo Global Logistics interview process

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

Initial Screening

First contact by a recruiter to assess candidate qualifications and fit.

What to demonstrate

First contact by a recruiter to assess candidate qualifications and fit
Depth in Problem Solving

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 undergo technical evaluations to demonstrate their skills.

What to demonstrate

Candidates undergo technical evaluations to demonstrate their skills
Depth in Problem Solving

How to prepare

Answer aloud and timed: How do you manage version control in your projects?
Answer aloud and timed: Can you describe a challenging bug you encountered and how you resolved it?

In-Person Interviews

Candidates participate in interviews focusing on technical discussions and behavioral fit.

What to demonstrate

Candidates participate in interviews focusing on technical discussions and behavioral fit
Depth in Problem Solving

How to prepare

Answer aloud and timed: What are the key differences between REST and SOAP APIs?
Answer aloud and timed: Describe a time when you had to work with a difficult team member. How did you handle it?

Where candidates lose points

Understand the Company’s Mission

Familiarize yourself with Echo Global Logistics and its mission. Knowing how your role contributes to the overall goals will help you articulate your value during the interview.

Practice Technical Skills

Engage in coding exercises and technical assessments to sharpen your skills. Platforms like HackerRank or LeetCode can be beneficial for practicing coding problems.

Prepare Behavioral Examples

Have specific examples ready that demonstrate your problem-solving skills and teamwork abilities. Use the STAR method (Situation, Task, Action, Result) for structuring your responses.

Ask Insightful Questions

Prepare thoughtful questions to ask your interviewers about the team, projects, and company culture. This shows your genuine interest and helps you assess if the company is the right fit for you.

Questions & practice

Write a function to sort an array of integers.

Medium · Coding / Algorithms

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?

How would you implement a search algorithm to find an item in a large dataset?

Medium · Coding / Algorithms

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 time complexity of your solution for a given problem?

Medium · Coding / Algorithms

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?

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

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.
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.
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.
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?

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?