Interview guides · EQT

EQT Software Engineer Interview Guide

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

The 60-second brief

As a Software Engineer at EQT, you play a vital role in building and scaling the technological backbone that drives North America's largest natural gas producer. Your work directly impacts operational efficiency, data management, and strategic decision-making across complex engineering and midstream assets. By developing robust software solutions, you help modernize traditional energy workflows, making operations safer, faster, and more data-driven. This position sits at the intersection of heavy industry and cutting-edge software engineering. You will collaborate closely with multidisciplinary teams—including reservoir engineers, operations planners, and data scientists—to translate complex physical challenges into scalable digital products.

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

Focus areas

Reserves/Reserve Reconciliation
Reservoir Engineering
Compression Optimization

The EQT interview process

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

Application Review

Initial review of your application by the recruiting team.

What to demonstrate

Initial review of your application by the recruiting team
Depth in Reserves/Reserve Reconciliation

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.

Recruiter Touchpoint

Discussion with a recruiter to discuss your background and the role.

What to demonstrate

Discussion with a recruiter to discuss your background and the role
Depth in Reserves/Reserve Reconciliation

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 Screening

Technical screening calls to assess your coding skills and technical knowledge.

What to demonstrate

Technical screening calls to assess your coding skills and technical knowledge
Depth in Reserves/Reserve Reconciliation

How to prepare

Answer aloud and timed: Can you walk through how you would design an efficient SQL query for large operational datasets?
Answer aloud and timed: What experience do you have with dynamic programming and complex data structures?

Panel Interviews

Comprehensive panel interviews with various team members to evaluate fit and skills.

What to demonstrate

Comprehensive panel interviews with various team members to evaluate fit and skills
Depth in Reserves/Reserve Reconciliation

How to prepare

Answer aloud and timed: Assess your communication style, interpersonal dynamics, and alignment with company values.
Answer aloud and timed: Can you walk me through your academic and professional background and explain what led you to this role?

Where candidates lose points

Brush up on SQL and data handling

Because many engineering workflows deal with heavy datasets, expect your ability to write clean queries and manage data flow to be tested.

Practice articulating your thought process

Interviewers value how you think just as much as the final answer, so narrate your problem-solving steps clearly and invite feedback.

Research the energy sector basics

Having a high-level understanding of how technology intersects with natural gas production or midstream operations will help you contextualize technical problems.

Prepare structured behavioral examples

Use the STAR method to organize your past experiences around teamwork, overcoming technical blockers, and managing tight timelines.

Showcase your curiosity

Ask insightful questions about the team's current technical stack, scaling challenges, and upcoming product roadmap during your interview loops.

Questions & practice

How do you manage memory and optimize performance in data-intensive applications?

Medium · Technical and 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?

What experience do you have with dynamic programming and complex data structures?

Medium · Technical and Domain Knowledge

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?

Walk me through your step-by-step approach to solving an unfamiliar algorithmic problem.

Medium · Problem-Solving and Quantitative Aptitud

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 do you prioritize tasks when faced with multiple ambiguous project requirements?

Medium · Problem-Solving and Quantitative Aptitud

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 walk through how you would design an efficient SQL query for large operational datasets?

Medium · Technical and 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?

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

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.
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.
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.
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?

Test your foundational software engineering knowledge, database skills, and familiarity with domain-specific e

Medium · Technical and Domain Knowledge

Test your foundational software engineering knowledge, database skills, and familiarity with domain-specific engineering concepts.

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?

What programming language would you prefer to use for this project, and why?

Medium · Technical and 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?

Describe how you would approach a data-heavy technical challenge, such as conducting a reserve reconciliation

Medium · Technical and Domain Knowledge

Describe how you would approach a data-heavy technical challenge, such as conducting a reserve reconciliation within a tight five-minute window.

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?

Evaluate your structured thinking, logical reasoning, and analytical capabilities under pressure.

Medium · Problem-Solving and Quantitative Aptitud

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?

Given a scenario with limited historical data, how would you estimate system capacity needs?

Medium · Problem-Solving and Quantitative Aptitud

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 debug a production issue when root causes are initially unclear?

Medium · Problem-Solving and Quantitative Aptitud

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 EQT candidates report.

Day 1 — Map the EQT loop

Write out the reported sequence: Application Review, Recruiter Touchpoint, Technical Screening, Panel 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 4 reported rounds, with the weakest marked.

Day 2 — Work Reserves/Reserve Reconciliation

Spend the session on Reserves/Reserve Reconciliation, which EQT candidates report being tested on.
Write one worked example in Reserves/Reserve Reconciliation and time yourself on it.

Deliverable: One timed worked example in Reserves/Reserve Reconciliation.

Day 3 — Work Reservoir Engineering

Spend the session on Reservoir Engineering, which EQT candidates report being tested on.
Write one worked example in Reservoir Engineering and time yourself on it.

Deliverable: One timed worked example in Reservoir Engineering.

Day 4 — Work Compression Optimization

Spend the session on Compression Optimization, which EQT candidates report being tested on.
Write one worked example in Compression Optimization and time yourself on it.

Deliverable: One timed worked example in Compression Optimization.

Day 5 — Answer out loud: Technical and Domain Knowledge

Answer aloud, timed: Test your foundational software engineering knowledge, database skills, and familiarity with domain-specific engineering concepts.
Answer aloud, timed: What programming language would you prefer to use for this project, and why?

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

Day 6 — Answer out loud: Behavioral and Culture Fit

Answer aloud, timed: Assess your communication style, interpersonal dynamics, and alignment with company values.
Answer aloud, timed: Can you walk me through your academic and professional background and explain what led you to this role?

Deliverable: Spoken answers to 2 reported Behavioral and Culture Fit question(s), under time.

Day 7 — Answer out loud: Problem-Solving and Quantitative Aptitude

Answer aloud, timed: Evaluate your structured thinking, logical reasoning, and analytical capabilities under pressure.
Answer aloud, timed: Walk me through your step-by-step approach to solving an unfamiliar algorithmic problem.

Deliverable: Spoken answers to 2 reported Problem-Solving and Quantitative Aptitude question(s), under time.