Interview guides · Helmerich & Payne

Helmerich & Payne Software Engineer Interview Guide

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

The 60-second brief

As a Software Engineer at Helmerich & Payne, you are at the intersection of high-stakes industrial operations and cutting-edge digital transformation. You are not just writing code; you are building the intelligence that powers the drilling industry. Your work directly impacts the efficiency, safety, and performance of our global operations, often involving complex systems that bridge the gap between cloud-based applications and field-deployed hardware. This role requires a blend of technical precision and the ability to navigate ambiguity. You will likely contribute to projects involving real-time data processing, API development, and system architecture that must perform reliably in diverse environments. Whether you are optimizing existing workflows or designing new tools from the ground up, your contributions are critical to maintaining our leadership in the energy sector.

This guide is scoped to a Software Engineer candidate at Helmerich & Payne.

Focus areas

Java
Data Structures & Algorithms (Coding Problems)
Problem Solving / Algorithmic Thinking

The Helmerich & Payne interview process

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

HR Screening

Initial screening to align on background, visa status, and role expectations.

What to demonstrate

Initial screening to align on background, visa status, and role expectations
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 Rounds

Two or three rounds focusing on coding challenges and system design discussions.

What to demonstrate

Two or three rounds focusing on coding challenges and system design discussions
Depth in Java

How to prepare

Answer aloud and timed: Can you explain High-order functions and their use cases?
Answer aloud and timed: What is your experience with MWD (Measurement While Drilling) terminology and tools?

Behavioral Panel

Final round assessing behavioral fit and cultural alignment.

What to demonstrate

Final round assessing behavioral fit and cultural alignment
Depth in Java

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 panel above and write down what you would ask to confirm before it.

Where candidates lose points

Structure your answers

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

Be honest about your experience

If you don't know the answer to a specific technical question, explain how you would go about finding the answer. We value transparency.

Research our values

Familiarize yourself with the core mission of Helmerich & Payne to ensure your responses align with our culture.

Ask meaningful questions

Use your time at the end of the interview to ask about team structure, current engineering challenges, and how the company fosters growth.

Questions & practice

Solve a variation of the Decode String problem.

Medium · Coding and 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?

Implement a solution for Reverse Words in a String.

Medium · Coding and 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?

Provide an efficient approach to the Word Break problem.

Medium · Coding and 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?

Write clean, functional code in Java or your primary language.

Medium · Coding and 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?

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?

Write the update path that detects a concurrent edit

Medium · optimistic concurrency · transactional outbox · audit history

resource carries version INT NOT NULL DEFAULT 1. resource_revision holds revision_id, resource_id, version, actor_user_id, change_kind, patch JSONB, request_id, created_at with UNIQUE (resource_id, version). outbox_event holds aggregate_type, aggregate_id, aggregate_version, event_type, payload, status. A PUT carries the version the client read. Write the exact statements for the single transaction that applies the edit, records the revision and enqueues 'resource.updated', and give the handler's branch on zero affected rows. Then say what PostgreSQL 16 does under READ COMMITTED when two of these updates hit one row at once.

Approach

One transaction, three writes, no network call inside it: UPDATE resource SET title = $3, version = version + 1, updated_at = now() WHERE resource_id = $1 AND tenant_id = $4 AND version = $2; then INSERT the resource_revision row at version $2 + 1; then INSERT the outbox_event row at the same aggregate_version. The event goes to a table rather than a broker because no transaction spans both.
Branch on the affected-row count before doing anything else. Zero has three causes — stale version, wrong tenant, row gone — so re-read once and map to 409 carrying the current version, or 404 for an id outside the caller's tenant, which also stops the endpoint confirming that another tenant's id exists.
State the engine behaviour instead of assuming it. Under READ COMMITTED the second UPDATE blocks on the row lock, and when the first commits PostgreSQL re-evaluates the WHERE clause against the newly committed row, so the version predicate now fails and the statement reports zero rows. Under REPEATABLE READ the identical collision raises SQLSTATE 40001 instead, so the handler must fold both shapes into one conflict response.
Keep UNIQUE (resource_id, version) even though the predicate already serialises writers. It is what makes a lost update unwritable if any other path ever reaches the revision table, and it converts a logic bug into 23505 rather than into a silently missing history row.

Follow-up

A client sends the version it read ten minutes ago and the resource has moved three versions. What is in your 409 so it can resolve the conflict without a full re-fetch?
Two editors, two disjoint fields, no overlap. Does your answer still refuse the second write, and should it?

Explain the difference between True North and Magnetic North.

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?

How do you handle API design and ensure scalability?

Medium · Technical and 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?

Can you explain High-order functions and their use cases?

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?

How do you apply design principles to ensure code maintainability?

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?

One log partition stops advancing while the others drain

Easy · poison message · head-of-line blocking · consumer lag

Search results for a subset of tenants are hours stale; the rest are current. The projection consumer reports lag of zero on 15 of 16 partitions and 400,000 on one. Its error rate is flat and its CPU is idle. outbox_event has no pending rows older than a second, so the relay has published everything it holds. Identify the mechanism, give the ordered checks, and state what you do in the first ten minutes versus what you change permanently.

Approach

Read the lag distribution first. A slow consumer lags everywhere; zero on fifteen partitions and 400,000 on one is not throughput. Idle CPU on the stuck partition means the consumer is not advancing its offset at all, which points at one message it cannot get past rather than at a rate problem.
Exonerate the producer before touching the consumer. No pending outbox rows older than a second means the relay published, so the event exists in the log. This separates never sent from sent and never applied, which are different code paths and usually different owners.
Read the message at the stuck offset and the handler's log lines for its event_id. A flat error rate with no progress has two explanations and you must distinguish them: the handler is throwing and the retry loop is swallowing it, or the handler is blocking on something and never returning. Idle CPU with no error lines favours the second.
Mitigate before diagnosing further. Move the offending event to a dead-letter store and commit the offset past it. Adding consumers does nothing here, because a partition is consumed by exactly one member of the group, and the blast radius is every aggregate hashed to that partition, not only the aggregate that produced the bad event.

Follow-up

The dead-lettered event carried aggregate_version 7 and the projection had applied 6. What must the replay do differently if 8 and 9 landed in the meantime?
How do you show staleness to the user while the partition is behind, given the API already returns the projection's watermark?

Suggested practice checklist

Built from the rounds and topics Helmerich & Payne candidates report.

Day 1 — Map the Helmerich & Payne loop

Write out the reported sequence: HR Screening, Technical Rounds, Behavioral Panel.
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 Helmerich & Payne 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 Data Structures & Algorithms (Coding Problems)

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

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

Day 4 — Work Problem Solving / Algorithmic Thinking

Spend the session on Problem Solving / Algorithmic Thinking, which Helmerich & Payne candidates report being tested on.
Write one worked example in Problem Solving / Algorithmic Thinking and time yourself on it.

Deliverable: One timed worked example in Problem Solving / Algorithmic Thinking.

Day 5 — Answer out loud: Technical and Domain Knowledge

Answer aloud, timed: Explain the difference between True North and Magnetic North.
Answer aloud, timed: How do you handle API design and ensure scalability?

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

Day 6 — Answer out loud: Coding and Algorithms

Answer aloud, timed: Solve a variation of the Decode String problem.
Answer aloud, timed: Implement a solution for Reverse Words in a String.

Deliverable: Spoken answers to 2 reported Coding and Algorithms question(s), under time.

Day 7 — Answer out loud: Behavioral and Leadership

Answer aloud, timed: Tell me about a time you had to manage a project through significant ambiguity.
Answer aloud, timed: How do you handle abrupt changes to project requirements?

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

Behavioural preparation

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

What is your experience with MWD (Measurement While Drilling) terminology and tools?

Medium · Technical and 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?