As a Software Engineer at Anadarko Petroleum, you serve as a critical bridge between complex energy operations and high-performance technical solutions. You are responsible for developing the tools and systems that empower our teams to make data-driven decisions in one of the most demanding and dynamic industries in the world. Your work directly impacts how we optimize exploration, drilling efficiency, and resource management. This role requires more than just coding proficiency; it demands a deep curiosity about how your software impacts the physical world. You will work within a collaborative, fast-paced environment where your technical contributions are expected to scale and provide long-term value. Whether you are building internal applications or streamlining data pipelines, you are a key contributor to the technological infrastructure that drives Anadarko Petroleum forward. ##### Tip Candidates report that the work culture is often described as "work-hard, play-hard," characterized by a supportive and fulfilling atmosphere where engineers are encouraged to be themselves.
Initial Contact
reportedCandidates are contacted for an initial discussion about the role and their background.
What to demonstrate
- Candidates are contacted for an initial discussion about the role and their background
- Depth in Behavioral Interviewing (STAR method)
How to prepare
- Answer aloud and timed: Tell me about yourself and your journey to this point.
- Answer aloud and timed: Where do you see yourself in 5 years?
Behavioral Assessment
reportedFocus on behavioral questions to assess cultural alignment and problem-solving capabilities.
What to demonstrate
- Focus on behavioral questions to assess cultural alignment and problem-solving capabilities
- Depth in Behavioral Interviewing (STAR method)
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 assessment above and write down what you would ask to confirm before it.
Technical Questions
reportedCandidates answer technical questions to demonstrate their problem-solving skills.
What to demonstrate
- Candidates answer technical questions to demonstrate their problem-solving skills
- Depth in Behavioral Interviewing (STAR method)
How to prepare
- Answer aloud and timed: What do you like to do outside of school or work?
- Answer aloud and timed: Walk me through a relevant project from your resume.
Onsite Panels or Dinners
reportedCandidates may participate in onsite interviews or informal dinners to further showcase their personality and technical depth.
What to demonstrate
- Candidates may participate in onsite interviews or informal dinners to further showcase their personality and technical depth
- Depth in Behavioral Interviewing (STAR method)
How to prepare
- Answer aloud and timed: How would you handle a situation where you disagree with a team member on a technical approach?
- Answer aloud and timed: Can you explain how you would solve [basic math/logic problem]?
PracHub editorial advice for the preparation topics above.
Use the STAR Method
When answering behavioral questions, structure your responses to highlight the situation, task, action, and result to ensure your impact is clear.
Be Conversational
Treat the interview as a professional discussion. If a question is unclear, don't hesitate to ask for clarification or provide context for your answer.
Research the Company
Have a basic understanding of Anadarko Petroleum's operations and its place in the industry.
Prepare Questions
Always have 2–3 thoughtful questions ready for the end of the session. This demonstrates your engagement and preparation.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
If you were faced with an ambiguous technical requirement, what steps would you take to clarify it?
If you were faced with an ambiguous technical requirement, what steps would you take to clarify it?
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?
Canonicalise a request body into a stable idempotency fingerprint
idempotency_key.request_fingerprint is a SHA-256 over the method, path and canonicalised body, and a retry whose fingerprint differs must be rejected with 422 rather than served the stored response. Write the canonicaliser. Bodies are JSON up to 256 KB nested at most 32 levels; clients vary key order, whitespace and unicode escaping, and some send 64-bit ids as JSON numbers. Produce a deterministic byte string such that semantically identical bodies match and any semantic difference does not. State your complexity and name two normalisations you refuse to perform.
Approach
- Parse once into a tree, then re-serialise under fixed rules: object keys sorted, array order preserved, one escaping convention, no insignificant whitespace. Parsing is O(n) and sorting keys is O(k log k) per object, so O(n log n) overall with O(depth) stack, and the 32-level cap is enforced during parsing because hostile nesting is how a canonicaliser becomes a stack overflow.
- Sort keys by their UTF-8 bytes and say why the obvious implementation is wrong in some runtimes: a default string comparison that orders by UTF-16 code units places surrogate pairs, meaning code points from U+10000 up, below U+E000 to U+FFFF, which is not UTF-8 byte order, so two services written in different languages disagree on the same document.
- Do not re-encode numbers through a double. IEEE-754 binary64 represents integers exactly only up to 2^53, so normalising a 19-digit id through a float changes it, and 1 against 1.0 cannot be reconciled without deciding whether they are the same value. Preserve the literal token, and require ids as strings at the API boundary if you want them comparable.
- Reject duplicate keys rather than picking one. JSON permits them and parsers disagree, most keeping the last, so any choice you make ties the fingerprint to a parser detail that the code handling the request does not necessarily share.
Follow-up
- A client sends the same logical request with an extra field your API ignores. Same key, different fingerprint, so you return 422. Is that the right answer?
- Where does the fingerprint get computed relative to request decompression and the body-size limit?
Track a rolling failure rate per destination for circuit decisions
The egress service delivers about 1,500 webhooks per second across roughly 40,000 destinations, each call bounded by a 10 second timeout. Maintain, per destination, the failure rate over the trailing 60 seconds so a caller can ask before dispatch whether the circuit should open. Attempts arrive as (destination_id, finished_at_ms, outcome). Requirement: amortised O(1) per attempt, with total memory bounded by the destination count rather than by traffic. Give the structure, its exact memory, and the rule that stops a destination with three attempts from opening a circuit.
Approach
- Name the exact-deque version and then reject it as the default. Holding timestamps and advancing a tail pointer past anything older than now minus 60 seconds is a correct two-pointer window at amortised O(1) per attempt, but its memory tracks in-window traffic, so one destination in a retry storm holds hundreds of thousands of entries while thousands of quiet destinations hold none.
- Use a ring of 60 one-second buckets per destination, each bucket a pair of counters for attempts and failures. On an attempt, advance the ring by the elapsed whole seconds, zeroing at most min(elapsed, 60) buckets, then increment the head. That is amortised O(1) with a fixed footprint per destination.
- State the footprint: 60 buckets times two 4-byte counters is 480 bytes of payload per destination, so 40,000 destinations is roughly 20 to 25 MB with per-entry overhead, bounded by the catalogue rather than by the rate. The cost is granularity, since the oldest bucket ages out in whole seconds, which is far tighter than the decision needs.
- Require a minimum sample before the circuit may open. A destination with three attempts and three failures reads as 100 percent and is not evidence; a floor of roughly 20 attempts in the window makes the ratio meaningful, and below that floor use a run of consecutive failures as the trigger instead.
Follow-up
- The fleet is 30 instances and each sees roughly a thirtieth of a destination's traffic. Where does the rate actually live, and what does a per-instance answer get wrong?
- A destination answers in 9.5 seconds and succeeds. It is not failing but it is consuming your per-destination concurrency. What signal should open the circuit here?
Keep soft-deleted accounts from blocking re-registration
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?
Replace offset paging on the resource feed with keyset
resource holds resource_id, tenant_id, owner_user_id, title, body_ref, version, status ('draft','active','archived','deleted'), created_at, updated_at, deleted_at, with an index on (tenant_id, status, updated_at DESC, resource_id DESC). The listing endpoint returns active resources for one tenant, newest update first, 50 per page, today with LIMIT 50 OFFSET n. Tenants reach page 400 and rows are created while they read. Write the keyset query, define what the cursor carries and how it is encoded, and say which part of the index each predicate uses. Assume PostgreSQL 16.
Approach
- Name the two failures separately. OFFSET 20000 makes the server produce and discard 20,000 rows, so page cost grows with depth rather than with page size. Independently, any write that changes how many rows sort above the offset moves the window between two fetches, and the direction decides which anomaly you get: an insert lands at the head of updated_at DESC and pushes already-returned rows down past the boundary, so they are returned a second time; a delete above the offset, or a row whose updated_at is bumped above the cursor, pulls rows up and one is never returned at all. Nothing in the response reveals either.
- Write the seek: WHERE tenant_id = $1 AND status = 'active' AND (updated_at, resource_id) < ($2, $3) ORDER BY updated_at DESC, resource_id DESC LIMIT 50. The row-value comparison is one index range rather than a disjunction, and both columns are NOT NULL, which is what makes that comparison well defined.
- Map each predicate onto the index: tenant_id and status are equality on the leading columns, (updated_at, resource_id) is the range, and the ORDER BY matches the index order so no Sort node appears and the scan stops after 50 rows. The DESC in the definition only matters for mixed directions — a plain ascending btree on the same columns is read backwards for this query.
- Put both sort columns in the cursor and nothing the client can tamper with into another tenant: base64 of (updated_at, resource_id), validated server-side, with tenant_id taken from the principal.
Follow-up
- The client asks for 'jump to page 400'. What do you offer instead, and what does the honest version cost?
- Sort order becomes user-selectable across four columns. How many indexes is that, and which would you refuse to add?
Walk me through a relevant project from your resume.
Walk me through a relevant project from your resume.
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?
Can you explain how you would solve [basic math/logic problem]?
Can you explain how you would solve [basic math/logic problem]?
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?
Is there any experience on your resume you would like to highlight that we haven't covered yet?
Is there any experience on your resume you would like to highlight that we haven't covered yet?
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?
Exports duplicate a row range about once a week
Roughly once a week an export writes a file containing a duplicated range of rows. The affected job_run rows show attempt = 1, status = succeeded, one started_at, and a lease_owner naming a different host from the one whose logs show the job starting. Leases last 30 seconds and are heartbeated every 10 from inside the handler; lease_expires_at is computed on the worker and compared against the database's now(). Find the mechanism, and give a fix that holds even if you cannot fix the clocks.
Approach
- Start from the fact that eliminates the obvious answer. attempt = 1 means no retry was recorded, so this is not a re-run after failure; two workers ran the same row concurrently and the takeover path never touched the counter. lease_owner naming a host other than the one that started the job is the same statement from the other side.
- Enumerate the mechanisms that cause a premature takeover, then find the signal that separates them. Either the lease genuinely expired because the heartbeat did not fire, which is what happens when the heartbeat runs on the handler's own thread and the handler makes a long blocking call, or it only appeared expired because two clocks disagree, since lease_expires_at is written from the worker's clock and evaluated against the database's. The discriminator is the distribution: incidents clustered on the longest exports indict the heartbeat, incidents clustered on one host indict skew. Measure both, and measure each host's offset against the database directly.
- Read the reclaim query precisely. In PostgreSQL now() is transaction start time, not statement time, so a reclaimer holding a long transaction compares against an older timestamp than expected; clock_timestamp() is the statement-time function. This is worth ruling in or out before you redesign anything, because it changes which rows look expired.
- Remove the second clock rather than trying to synchronise it. Issue and extend the lease in the database, with lease_expires_at = now() + interval '30 seconds' in both the claim and the heartbeat, so exactly one clock is ever compared and worker skew stops mattering to this predicate.
Follow-up
- The displaced worker has already streamed half the file to object storage. What makes that side effect safe to repeat?
- You now count takeovers. What alert fires on that counter, and at what threshold?
Built from the rounds and topics Anadarko Petroleum candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Anadarko Petroleum loop
- Write out the reported sequence: Initial Contact, Behavioral Assessment, Technical Questions, Onsite Panels or Dinners.
- 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.
02Work Behavioral Interviewing (STAR method)
- Spend the session on Behavioral Interviewing (STAR method), which Anadarko Petroleum candidates report being tested on.
- Write one worked example in Behavioral Interviewing (STAR method) and time yourself on it.
Deliverable: One timed worked example in Behavioral Interviewing (STAR method).
03Work Motivation & Career Planning
- Spend the session on Motivation & Career Planning, which Anadarko Petroleum candidates report being tested on.
- Write one worked example in Motivation & Career Planning and time yourself on it.
Deliverable: One timed worked example in Motivation & Career Planning.
04Work Resume Walkthrough
- Spend the session on Resume Walkthrough, which Anadarko Petroleum candidates report being tested on.
- Write one worked example in Resume Walkthrough and time yourself on it.
Deliverable: One timed worked example in Resume Walkthrough.
05Answer out loud: Behavioral and Career Motivation
- Answer aloud, timed: Tell me about yourself and your journey to this point.
- Answer aloud, timed: Where do you see yourself in 5 years?
Deliverable: Spoken answers to 2 reported Behavioral and Career Motivation question(s), under time.
06Answer out loud: Technical and Situational Analysis
- Answer aloud, timed: Walk me through a relevant project from your resume.
- Answer aloud, timed: How would you handle a situation where you disagree with a team member on a technical approach?
Deliverable: Spoken answers to 2 reported Technical and Situational Analysis question(s), under time.
07Dry run for Anadarko Petroleum
- Run one full mock under time, then write down the two questions you most want to ask your interviewers.
Deliverable: A completed timed mock and two questions to ask.
Expand any day for tasks and deliverables. Your progress is saved on this device.
Behavioural rounds judge the decision you made and what it cost.
Tell me about yourself and your journey to this point.
Tell me about yourself and your journey to this point.
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?
Where do you see yourself in 5 years?
Where do you see yourself in 5 years?
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?
What are your short-term and long-term career goals?
What are your short-term and long-term career goals?
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?
What draws you to a career at Anadarko Petroleum specifically?
What draws you to a career at Anadarko Petroleum specifically?
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?
What do you like to do outside of school or work?
What do you like to do outside of school or work?
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?
How would you handle a situation where you disagree with a team member on a technical approach?
How would you handle a situation where you disagree with a team member on a technical approach?
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?
- 01
Tell me about yourself and your journey to this point.
- 02
Where do you see yourself in 5 years?
- 03
What are your short-term and long-term career goals?
- 04
What draws you to a career at Anadarko Petroleum specifically?
How difficult are the technical portions of the interview?
The technical portion is generally considered approachable. The focus is on your ability to reason through problems and explain your logic rather than memorizing complex algorithms.
Anadarko Petroleum Software Engineer candidate reports ↗How long does the hiring process usually take?
The process is often fast-paced, with some candidates reporting turnaround times of under a week from the initial interview to a final decision.
Anadarko Petroleum Software Engineer candidate reports ↗What should I ask the interviewers?
Use this time to learn about the company culture and the team's current challenges. Asking about their personal experiences at the company shows genuine interest.
Anadarko Petroleum Software Engineer candidate reports ↗Is there anything I should avoid?
Avoid being overly "nerdy" to the exclusion of social interaction. The team values candidates who are down-to-earth and able to hold a meaningful, two-way conversation.
Anadarko Petroleum Software Engineer candidate reports ↗What topics does Anadarko Petroleum test in interviews?
Anadarko Petroleum interviews most often cover Behavioral Interviewing (Competency-Based), Machine Learning (ML), Behavioral Interviewing (STAR method), Cultural Fit Assessment, and Random Forest. The exact emphasis depends on the specific role you apply for.
Anadarko Petroleum Software Engineer candidate reports ↗Sources & methodology 3 sources ↗
No official company page is cited. Rounds and questions come from candidate reports and PracHub editorial material; each source shows the date it was read.
- 01Anadarko Petroleum Software Engineer candidate reports ↗
Company-reported rounds, questions and FAQ.
Candidate reports · Accessed 2026-09-22 - 02PracHub Software Engineer practice ↗
PracHub practice material, not company-reported.
PracHub page · Accessed 2026-09-22 - 03PracHub preparation framework ↗
PracHub preparation guidance.
PracHub page · Accessed 2026-09-22
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