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Berkeley Research Group Software Engineer Interview Guide

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

The 60-second brief

A Software Engineer at Berkeley Research Group (BRG) plays a pivotal role at the intersection of high-stakes consulting and advanced technology. Unlike traditional tech firms, BRG is a global strategic advisory and expert consulting firm. This means our engineers do not just build products; they build the sophisticated analytical frameworks, data pipelines, and specialized applications that allow our experts to provide data-driven testimony and strategic advice in multi-billion dollar disputes and corporate investigations. Your work will directly impact the ability of our consultants to process, visualize, and interpret massive, complex datasets. Whether you are developing bespoke forensic tools or scaling internal platforms, you are building the engine that drives BRG’s reputation for excellence.

This guide is scoped to a Software Engineer candidate at Berkeley Research Group.

Focus areas

  • Data Analyst-Style Case Questions
  • Technical Interviewing
  • Pair Programming

The Berkeley Research Group interview process

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

Recruiter Touchpoint

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

What to demonstrate

  • Initial contact with a recruiter to assess background and fit for the role
  • Depth in Data Analyst-Style Case Questions

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

In-depth technical evaluations including coding exercises and problem-solving scenarios.

What to demonstrate

  • In-depth technical evaluations including coding exercises and problem-solving scenarios
  • Depth in Data Analyst-Style Case Questions

How to prepare

  • Answer aloud and timed: Write a function to find the first non-repeating character in a string. What is the time complexity?
  • Answer aloud and timed: How do you handle exceptions in a multi-threaded environment to ensure data consistency?

Behavioral Interview

Conversations with hiring managers focusing on past experiences and cultural fit.

What to demonstrate

  • Conversations with hiring managers focusing on past experiences and cultural fit
  • Depth in Data Analyst-Style Case Questions

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

Final Decision

Review of all assessments and discussions to make a hiring decision.

What to demonstrate

  • Review of all assessments and discussions to make a hiring decision
  • Depth in Data Analyst-Style Case Questions

How to prepare

  • Answer aloud and timed: What steps do you take to validate the accuracy of a data migration project?
  • Answer aloud and timed: Explain how you would design a system to track changes in a dataset over time (SCD Type 2).

Where candidates lose points

Prioritize Data Logic

When practicing coding challenges, focus on problems involving data parsing, aggregation, and transformation. These are far more common in our interviews than pure competitive programming puzzles.

Be Professional in Communication

As a firm that interacts with high-level legal and corporate clients, we look for professional communication from the very first email. Treat every interaction as a reflection of how you would represent the firm.

Some candidates have reported being asked to clear a full day for interviews on short notice

While we strive for better scheduling, be prepared for a potentially condensed and intensive interview day.

Clarify the Requirements

In pair programming or case study rounds, always ask clarifying questions before you start coding. In our world, a "correct" solution to the wrong problem is a failure.

Questions & practice

Explain the difference between an abstract class and an interface, and when you would use each.

Medium · Technical & Coding

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?

Write a function to find the first non-repeating character in a string. What is the time complexity?

Medium · Technical & Coding

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 how you would implement a caching layer for a frequently accessed data service.

Medium · Technical & Coding

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?

How would you optimize a SQL query that is running slowly on a table with millions of rows?

Medium · Technical & Coding

Approach

  1. Name the grain you start from and join outward from it.
  2. Check whether any join is one-to-many before aggregating, or the sums inflate.
  3. Say which index the query would use, and what makes it unusable.
  4. 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?

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

  1. 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.
  2. 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.
  3. 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.
  4. 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?

You are given two large datasets with no common unique identifier. How do you approach merging them?

Medium · Data & Analytical Logic

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 steps do you take to validate the accuracy of a data migration project?

Medium · Data & Analytical Logic

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?

Explain how you would design a system to track changes in a dataset over time (SCD Type 2).

Medium · Data & Analytical 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 would you programmatically identify outliers in a dataset of financial transactions?

Medium · Data & Analytical Logic

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?

Exports duplicate a row range about once a week

Hard · leases · clock skew · idempotency

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

  1. 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.
  2. 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.
  3. 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.
  4. 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?

Suggested practice checklist

Built from the rounds and topics Berkeley Research Group candidates report.

Day 1 — Map the Berkeley Research Group loop

  • Write out the reported sequence: Recruiter Touchpoint, Technical Assessments, Behavioral Interview, Final Decision.
  • 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 Data Analyst-Style Case Questions

  • Spend the session on Data Analyst-Style Case Questions, which Berkeley Research Group candidates report being tested on.
  • Write one worked example in Data Analyst-Style Case Questions and time yourself on it.

Deliverable: One timed worked example in Data Analyst-Style Case Questions.

Day 3 — Work Technical Interviewing

  • Spend the session on Technical Interviewing, which Berkeley Research Group candidates report being tested on.
  • Write one worked example in Technical Interviewing and time yourself on it.

Deliverable: One timed worked example in Technical Interviewing.

Day 4 — Work Pair Programming

  • Spend the session on Pair Programming, which Berkeley Research Group candidates report being tested on.
  • Write one worked example in Pair Programming and time yourself on it.

Deliverable: One timed worked example in Pair Programming.

Day 5 — Answer out loud: Technical & Coding

  • Answer aloud, timed: How would you optimize a SQL query that is running slowly on a table with millions of rows?
  • Answer aloud, timed: Explain the difference between an abstract class and an interface, and when you would use each.

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

Day 6 — Answer out loud: Data & Analytical Logic

  • Answer aloud, timed: You are given two large datasets with no common unique identifier. How do you approach merging them?
  • Answer aloud, timed: What steps do you take to validate the accuracy of a data migration project?

Deliverable: Spoken answers to 2 reported Data & Analytical Logic question(s), under time.

Day 7 — Answer out loud: Behavioral & Situational

  • Answer aloud, timed: Tell me about a time you had to explain a technical concept to a non-technical stakeholder.
  • Answer aloud, timed: Describe a situation where you had to move a meeting or a deadline due to a conflict. How did you handle the communication?

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

Behavioural preparation

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

How do you handle exceptions in a multi-threaded environment to ensure data consistency?

Medium · Technical & Coding

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?

Tell me about a time you had to explain a technical concept to a non-technical stakeholder.

Medium · Behavioral & Situational

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?

Describe a situation where you had to move a meeting or a deadline due to a conflict. How did you handle the c

Medium · Behavioral & Situational

Describe a situation where you had to move a meeting or a deadline due to a conflict. How did you handle the communication?

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?

Give an example of a time you disagreed with a teammate's technical approach. How was it resolved?

Medium · Behavioral & Situational

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?

What is the most complex technical challenge you've faced, and how did you overcome it?

Medium · Behavioral & Situational

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?