Target runs two almost unrelated hiring machines. For hourly store jobs the loop is short and increasingly automated: apply in Workday, then a HireVue recorded video interview with roughly five behavioural prompts plus a yes/no physical-requirements and availability question, with a phone call or a brief in-store meeting only sometimes bolted on afterwards. Candidates repeatedly describe hiring or rejection decisions arriving within hours of submitting the video, and several report a per-question attempt limit rather than the unlimited retakes they expected. Leadership hiring is a much longer behavioural gauntlet: team lead roles usually mean one or two conversations with an ETL, store director or HR partner built around four or five situational questions scored in a Situation/Behavior/Outcome frame, while ETL candidates go through a three-guide (A/B/C) chain that climbs from store director to district leader plus HR business partner and, in more recent rounds, up to a group VP or HR director. Longtime posters note Target quietly shifted the ETL guides away from pure "tell me about a time" STAR toward a broader dialogue about culture, inclusivity, retaining talent and 30/60/90 check-ins, and that stories are expected to be store-wide in scope rather than about finishing a truck. Distribution centre hiring is the leanest of all, historically a phone screen and a single in-person conversation that can end in an on-the-spot offer. Target's India technology arm in Bengaluru hires on a completely different pattern: an AMCAT or HackerEarth/HackerRank online assessment mixing aptitude, code-output MCQs and one to two coding problems, followed by two or three panel interviews that lean hard on the candidate's own resume and projects plus SQL, DBMS and Java or Python fundamentals, closing with an HR round; experienced hires additionally see low-level design and a machine-coding round.
These 37 writeups cover retail store operations, retail leadership, warehouse distribution and other roles, US stores/DCs + India tech (Bengaluru). 36 of them were posted under a pseudonym (Reddit, GeeksforGeeks or forum handles), so we could not verify the authors’ identities.
Typical rounds
2.11-4 range
Outcomes shared
4/6offer / not
Most common round
Technical
Sources span
2012 - 2026
Most frequently reported · Behavioral(30), Data structures & algorithms(13), Arrays & strings(12), STAR stories(12), Aptitude(11)
Target’s official process
Target describes a six-stage flow: apply through Workday (some roles add a short availability or skills assessment), recruiter review and possible outreach, interviewing, offer, onboarding via Target Welcome, then training and development. It says interviews may be by phone, virtual, in person or as pre-recorded video responses, and that a candidate may see more than one format depending on the role. A companion recorded-video-interview page says the session takes about half an hour, allows unlimited practice questions that reviewers never see, gives timed prompts per question, and states that Target does not allow retakes; a recruiter or hiring manager reviews the video alongside the resume and responds within five business days. Target's interview guide frames the conversation around five areas (job knowledge, inclusivity, problem solving, connection, drive), suggests answers of roughly five minutes, and explicitly forbids using AI assistance to generate answers. All offers are contingent on a background check run through the vendor Accurate Background.
An external applicant recorded five self-taped answers covering interest in the role, adapting after something went wrong, working with people who see things differently, and collaborating toward a shared goal, each explicitly asking for the situation, actions and outcome. A sixth item was not recorded at all but a simple yes/no acknowledgement.
Covered · Behavioral, STAR stories, Conflict handling, Shift availability
The same recorded format a year later, with one prompt swapped for a hypothetical: what the candidate would do on the sales floor on spotting a guest who looks like they need help. The rest stayed situation/action/outcome behavioural items.
Covered · Behavioral, Customer scenarios, Conflict handling, STAR stories
A 2025 recording of the same question set, closing with a non-recorded acknowledgement that store roles require climbing ladders, a flexible schedule covering nights, weekends and holidays, and regular attendance.
Covered · Behavioral, STAR stories, Shift availability
Another 2025 recording of the set, with the second prompt reworded to ask how past experience shapes the candidate's current approach, and the guest-on-the-sales-floor hypothetical retained.
Covered · Behavioral, Customer scenarios, STAR stories
Applied to every holiday listing at one store and was invited to interview for the one role they had deliberately skipped, an overnight inbound shift. They recorded the interview anyway.
Covered · Behavioral, Shift availability
2
Recruiter callback and offerFinal
A callback followed with an offer that turned out to be for front-end guest advocate rather than the overnight role they had interviewed for, suggesting the store treats the video as generic across postings. The candidate declined.
The candidate waited about forty-five minutes at the store because the scheduled interviewer was away, then interviewed with a substitute who asked whether they were open to other positions.
Covered · Behavioral, Shift availability
2
Grocery team lead conversationHiring manager
Because they expressed interest in stocking, the grocery team lead was pulled over for a short follow-up covering self-introduction and where they saw their future at Target. A rejection email arrived at midnight the same day.
On-Demand Front of Store Attendant (cart attendant)
Internship
Outcome not shared2 rounds
1
HireVue recorded video interviewPhone screen
Six recorded questions submitted from home; the candidate assumed this was the entire process.
Covered · Behavioral, Customer scenarios
2
In-store interviewHiring manager
Within hours the store called them in for an in-person conversation, checked whether they would take on more weekends, and told them which work centre they would likely land in. Forum regulars advised simply reporting to guest services on arrival.
The candidate found the recorded format gave almost no reading or thinking time before recording began, and reported a hard cap of three attempts per question rather than free retakes. They were hired off the video alone, never receiving the availability call that hiring leaders in the same thread said normally follows a yes.
Invited in the morning, recorded late the same night, and rejected by email roughly an hour after submission, which the candidate read as an automated screen rather than a human review.
A phone screen came roughly a week after applying in store.
Covered · Behavioral, Shift availability
2
One-on-one in-store interviewHiring manager
A same-day or next-day in-person conversation, closed with the standard line about contacting candidates after all interviews were done. The offer for a sales floor role came about a week later.
Four situational prompts scored against a Situation/Behavior/Outcome frame, covering influencing another team to hit a deadline, holding someone accountable for a task or behaviour, and adapting a complex message for different audiences. Self-introduction, strengths and weaknesses, and why the role appeals came first.
Covered · STAR stories, Conflict handling, Behavioral, Leadership Principles
A second-stage interview that ran about an hour and fifteen minutes, conversational enough that the interviewer shared internal store detail. No store walkthrough was offered, and the candidate was told that under the current hiring system a return visit would itself signal selection.
A meet-and-greet with district leadership after a store realignment that was much softer than a scored interview: what field or ETL roles the candidate wanted next, and what they do outside work.
A three-guide (A, B, C) chain in which the candidate's first sitting ran off guide B with a store director. They had heard the chain was being rerouted to store director, then district senior director plus HR business partner, then group VP or HR director.
Covered · Leadership Principles, Behavioral, STAR stories
2
District and HR partnerPanel
The district-level round paired with an HR business partner, using the remaining guide.
The first two of four scheduled ETL interviews were run as Situation, Behavior, Outcome questions, which the candidate felt they had underperformed on because their answers ran short.
Covered · STAR stories, Behavioral, Leadership Principles
2
Rounds 3-4: Later-stage leadership roundsPanel
Two further rounds remained. Experienced posters warned them the later ETL guides pivot to culture, inclusivity, retaining team members, 30/60/90 check-ins and how they elevate departments, rather than task execution like truck unload or price change.
Three separate interviews with executive team leaders, which the candidate found largely redundant with one another; the graders wanted answers framed around the best business outcome rather than the immediate task.
A single interview with the pharmacy executive team leader, following earlier interviews the same candidate had done for other in-store roles. Pharmacists in the thread described what they screen for: working at pace in a cramped, high-stress space, asking why a task is done rather than executing blindly, and steadily learning brand-generic drug pairings.
A single in-person interview at the distribution centre, conducted by one person while most other candidates that day faced two interviewers. An internal referral did not change the outcome; a rejection email arrived three days later.
Across two DC promotions in eighteen months the candidate found the questions were consistently situational and answered in STAR form. They walked in with prepared stories on safety, problem solving, teamwork and leadership and reshaped them to whatever was asked.
Covered · Safety procedures, STAR stories, Conflict handling, Behavioral
Eleven items: ten code-output MCQs and one weighted coding problem applying a conditional discount across an array of prices, in any language.
Covered · Arrays & strings, Aptitude, Debugging
2
Technical panelTechnical
Two interviewers worked entirely from the resume: Java OOP, a small array-sum program, and a hands-on SQL exercise where the candidate had to sketch sample tables with dummy data before writing joins and constraint queries. Version control usage also came up.
Covered · OOP, SQL, DBMS, Past projects, Resume deep-dive
3
Second technical panelTechnical
Another two-person panel that had read the first panel's notes and deliberately probed the weak points from round one, covering Java access modifiers, inheritance and abstract classes. Only sixteen of about eighty candidates reached the interview stage.
Ninety minutes in three parts: a reading-and-reasoning aptitude section, a section on predicting output, spotting errors and stating time complexity, and a decisive sixty-minute coding section with two problems (an interval/gap problem over positioned houses and an adjacency check over a binary matrix).
Two interviewers for around fifty minutes, going deep on CV projects and internship specifics, then DBMS and SQL, sorting and search algorithms and complexity, with pseudocode written live and the logic explained.
Covered · Past projects, DBMS, SQL, Data structures & algorithms
Ten objective questions from data structures, C and aptitude, plus one coding problem converting a prefix expression to postfix.
Covered · Data structures & algorithms, Aptitude
2
Technical interviewTechnical
Around forty-five minutes that opened with what the candidate knew about Target, spent roughly thirty minutes on their project, then moved to Java: inheritance, abstract classes versus interfaces, writing a singleton, upcasting and downcasting, and predicting code output.
Covered · Past projects, OOP, Domain knowledge
3
Resume and situational interviewBehavioral
Resume-driven questions mixed with situational ones, more DBMS querying, and the standard why-Target and five-year questions.
Covered · Resume deep-dive, Behavioral, SQL, Past projects
Thirty-one items, thirty of them C/C++ and aptitude objectives plus one coding submission judged against all test cases.
Covered · Aptitude, Data structures & algorithms
2
Technical interviewTechnical
A long, code-heavy round: search in a row-and-column-sorted matrix (with the interviewer falsely claiming the solution was wrong to see whether the candidate would cave), string permutations, finding a node's grandparent, and mirroring a binary tree, each followed by a push to convert recursion to iteration. Interleaved with key types, OS fragmentation, warehouse versus database, triggers, and how their project's IDE reached the database server.
Covered · Data structures & algorithms, Trees, DBMS, SQL, Operating systems, Past projects
3
HR and behaviouralBehavioral
Teamwork and conflict, an embarrassing moment, which CV project they preferred and why, an explanation of a gap between degrees, and long-term goals.
Covered · Behavioral, Conflict handling, STAR stories, Resume deep-dive
Thirty-one questions in sixty minutes, thirty quantitative and CS-fundamentals objectives plus a coding problem counting trailing zeroes in a factorial. About twenty-seven students advanced.
Covered · Aptitude, Data structures & algorithms
2
Technical interviewTechnical
Duplicate removal from an array, explaining merge sort and quicksort and which data structure quicksort evokes, finding the nearest perfect square, then project questions.
Covered · Arrays & strings, Data structures & algorithms, Past projects
3
HR interviewBehavioral
Problems hit during the project and the candidate's proudest achievement, among a handful of others.
Covered · Behavioral, Past projects, STAR stories
4
Mixed interviewPanel
Resume questions plus, for a non-CS student, their favourite subject in their own department and how they would apply that knowledge inside the retail industry.
Three timed sections: fifteen aptitude and reasoning MCQs, fifteen code-snippet MCQs, then two coding problems, one medium on arrays and one hard combining graphs and dynamic programming.
Resume-led, starting with de-duplicating a string array and extending into writing test cases for that code, then hash map internals, the collections hierarchy, dependency injection, server port configuration, database connectivity in Spring Boot, load balancing and circuit-breaker states.
Covered · Data structures & algorithms, Testing, OOP, API design, Scalability
3
Design and systems interviewLow-level design
A low-level design of an Instagram-like system, plus containerisation, a top-N-without-sorting problem, request/response handling, per-environment configuration, and a table-to-table SQL insert.
Covered · Low-level design, SQL, API design, Scalability
Thirty MCQs on aptitude and predicting output or error type, plus a timing-simulation coding problem about when a phone beep falls in the gaps between songs. Roughly thirty candidates advanced.
Covered · Aptitude, Debugging, Data structures & algorithms
2
Technical interviewTechnical
Bottom-up level-order traversal of a binary tree using a queue and a stack, and a substring check, both written out in code.
Covered · Trees, Arrays & strings, Data structures & algorithms
3
Second technical interviewTechnical
Opened with writing any sorting algorithm as a warm-up, then an extended discussion of the candidate's technical internship with some softer questions mixed in.
Covered · Data structures & algorithms, Past projects
4
HR interviewBehavioral
Twelve to fifteen questions in about half an hour, each demanding a concrete instance where the candidate had demonstrated a named skill, with the interviewer noting keywords throughout.
Covered · Behavioral, STAR stories, Conflict handling
A December 2023 virtual pool drive open to CS, IS, AIML and EC branches. MCQs across reasoning, quantitative and technical topics plus two coding problems, one a digit-frequency counting task and one graph-based. Twenty-nine students were shortlisted.
Covered · Aptitude, Arrays & strings, Graphs
2
Combined technical and HR interviewPanel
A seventy-five-minute Zoom call with two interviewers, one a Python-fluent data engineer. After an introduction covering prior internship and CV projects, the candidate was asked to rate their Python skill and then coded live under added constraints, including filtering mixed-type tuple contents without conditional statements and reporting the maximum and most frequent integers in a list concisely.
Covered · Data structures & algorithms, OOP, Past projects, Behavioral
Ten objectives spanning data structures, Java, OS and C, plus a reachability coding problem over coordinate transformations.
Covered · Data structures & algorithms, Operating systems, OOP
2
Technical interviewTechnical
Heavily database-oriented: keys used in the project, OOP concepts, subqueries and correlated subqueries, joins including predicting a left outer join result over two given tables, a marks-threshold query, partitioning, memory reallocation limits, and binary search.
Covered · SQL, DBMS, OOP, Past projects, Operating systems
3
Technical and HR interviewBehavioral
Opened with an open-ended 'impress me' prompt, then normalisation through third normal form including decomposing a supplied unnormalised table, a substring program, database types, and closing questions on why they should and should not be hired and what kind of teammates they prefer.
MCQs on comprehension, reasoning, quantitative and CS topics, plus two coding problems (counting duplicates in an array, and an optimal-flow problem) scored against hidden test cases; partial test-case success still advanced the candidate.
Covered · Aptitude, Arrays & strings, Data structures & algorithms
2
Technical interviewTechnical
An hour with two interviewers on a video tool. It began on front-end topics inferred from the resume, pivoted to back end when the candidate corrected them, then ranged across linked lists versus arrays and their trade-offs, merging and de-duplicating arrays, word counting, trees, heaps and BSTs, database types and normalisation, OS paging, semaphores and deadlock, C memory allocation, bitwise operations and shell commands.
Covered · Data structures & algorithms, Trees, DBMS, Operating systems, Networking, Past projects
3
HR interviewBehavioral
A half-hour Zoom call almost entirely driven by the resume: handling project conflict, persuading teammates on a disputed idea, strengths and weaknesses, listed certifications and why Target.
A HackerRank test with one coding problem plus MCQs on data structures, algorithms and aptitude.
Covered · Data structures & algorithms, Aptitude
2
Technical interviewTechnical
In-depth project discussion plus live code for a missing-number problem, string frequency counting over a container and an in-place swap, then SQL covering all four join types and union versus union all.
Covered · Past projects, Arrays & strings, SQL
3
Second technical interviewTechnical
More project discussion and OOP, concentrating on method overriding, its benefits and real-world analogies.
Covered · OOP, Past projects
4
HR interviewBehavioral
Extracurriculars, why they wanted to be a software engineer as an ECE student, and career goals. Eight candidates reached HR and six were selected; this candidate was one of the two rejected.
Two DSA problems: a common-substring problem across a set of strings, and the maximum leaf-to-leaf distance in a tree.
Covered · Arrays & strings, Trees, Data structures & algorithms
2
Technical interviewTechnical
An hour and fifteen minutes with two long-tenured Target engineers on an assessment platform. A string-manipulation problem with repeated challenges to the approach, spot checks on indexing and encapsulation, a puzzle, then an exhaustive teardown of an e-commerce project including how to keep data sorted in C++ without a self-sorting structure, which the candidate answered with an insertion-ordered linked list and then optimised with a midpoint pointer.
Covered · Past projects, DBMS, OOP, Puzzles, Data structures & algorithms
3
Second technical interviewTechnical
A discussion-style round that tried to connect everything on the resume: applying the candidate's machine-learning work to their e-commerce project, and how they would implement search on that site.
Covered · Past projects, Resume deep-dive, System design
A single reported round spanning SQL (execution order, join versus union, having versus group by, updates, cleaning a date column, pivoting without PIVOT, nth-highest salary, percent rank, year-on-year growth by category), pandas work including renaming columns, dropping nulls and JSON extraction, chart-type selection, and Excel lookups, pivot tables and running totals. The candidate answered everything except the date-cleaning task and advanced.
The first of three rounds, run entirely in JavaScript: de-duplicating an array, top-K frequent elements, transforming and filtering an array of objects in a single pass, an explanation of call versus bind plus writing a polyfill for call, and finally a small React build with two lists and buttons that move the head item between them.
A short screen on framework and API signature basics.
Covered · API design, Domain knowledge
2
Machine codingTechnical
A hands-on round working inside a supplied codebase: fix the defects, add a feature and write tests for it. Two further rounds followed that the writeup did not detail; the candidate rated the experience positively despite no offer.
Target runs two almost unrelated hiring machines. For hourly store jobs the loop is short and increasingly automated: apply in Workday, then a HireVue recorded video interview with roughly five behavioural prompts plus a yes/no physical-requirements and availability question, with a phone call or a brief in-store meeting only sometimes bolted on afterwards. Candidates repeatedly describe hiring or rejection decisions arriving within hours of submitting the video, and several report a per-question attempt limit rather than the unlimited retakes they expected. Leadership hiring is a much longer behavioural gauntlet: team lead roles usually mean one or two conversations with an ETL, store director or HR partner built around four or five situational questions scored in a Situation/Behavior/Outcome frame, while ETL candidates go through a three-guide (A/B/C) chain that climbs from store director to district leader plus HR business partner and, in more recent rounds, up to a group VP or HR director. Longtime posters note Target quietly shifted the ETL guides away from pure "tell me about a time" STAR toward a broader dialogue about culture, inclusivity, retaining talent and 30/60/90 check-ins, and that stories are expected to be store-wide in scope rather than about finishing a truck. Distribution centre hiring is the leanest of all, historically a phone screen and a single in-person conversation that can end in an on-the-spot offer. Target's India technology arm in Bengaluru hires on a completely different pattern: an AMCAT or HackerEarth/HackerRank online assessment mixing aptitude, code-output MCQs and one to two coding problems, followed by two or three panel interviews that lean hard on the candidate's own resume and projects plus SQL, DBMS and Java or Python fundamentals, closing with an HR round; experienced hires additionally see low-level design and a machine-coding round.
What topics does Target test in interviews?
Commonly reported topics include Behavioral, STAR stories, Customer scenarios, Shift availability, Conflict handling, Resume deep-dive.
These guides summarize public, first-hand interview experiences shared by candidates. They describe the shape of each loop and the topics that came up, not a leaked question bank, and every experience links back to its original source. Processes change often; treat this as directional prep, not a script.