A Software Engineer at PCS Global Tech serves as a core contributor to the company’s mission of bridging the gap between academic learning and industry-ready technical execution. You will be responsible for designing, developing, and maintaining software solutions that support complex enterprise environments. Your work is central to the company’s training and development ecosystem, requiring a blend of high-level problem solving and rigorous adherence to technical standards. In this role, you will often operate at the intersection of application development and database management. The position demands not just an ability to write clean, efficient code, but also a deep understanding of the full software development lifecycle. Whether you are working on internal tools or client-facing projects, your contribution ensures that PCS Global Tech maintains its technical reputation and delivers high-quality software outcomes. ##### Tip The role is heavily focused on practical application. Be prepared to discuss not just how you write code, but how you optimize it for performance and scalability in real-world scenarios.
Initial Screening
reportedThe first step where candidates are screened for basic qualifications and fit.
What to demonstrate
- The first step where candidates are screened for basic qualifications and fit
- Depth in SQL
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.
Online Assessment
reportedA critical filter that evaluates technical skills through an online test.
What to demonstrate
- A critical filter that evaluates technical skills through an online test
- Depth in SQL
How to prepare
- Answer aloud and timed: Can you walk through a problem involving data structures such as lists, tuples, or arrays?
- Answer aloud and timed: What are the differences between various collection types in your primary language?
Technical Assessment
reportedFurther evaluation of technical knowledge through live video interviews.
What to demonstrate
- Further evaluation of technical knowledge through live video interviews
- Depth in SQL
How to prepare
- Answer aloud and timed: How do you approach debugging a piece of code that is failing in a production-like environment?
- Answer aloud and timed: What is the difference between inner, outer, and cross joins in SQL?
Final Interviews
reportedConcluding interviews that assess overall fit and technical capabilities.
What to demonstrate
- Concluding interviews that assess overall fit and technical capabilities
- Depth in SQL
How to prepare
- Answer aloud and timed: Can you explain the concept of normalization and why it is important for database design?
- Answer aloud and timed: Write a query to retrieve specific records from a table based on multiple conditions.
PracHub editorial advice for the preparation topics above.
Review your resume
Expect every line of your resume to be fair game for technical questioning. If you list a language, be ready to defend your proficiency in it.
Prepare for video etiquette
Since interviews are remote, ensure your lighting and audio are clear. Being able to communicate your thoughts while screen-sharing code is a critical skill.
Practice live coding
Use a local IDE or a simple text editor to practice writing code while talking through your logic. Some interviewers may restrict the use of online compilers.
Ask questions
At the end of your interview, ask about the training program or the team's current projects. It shows genuine interest and helps you evaluate if the company is the right fit for your career growth.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
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?
Archive a resource graph without breaking live references or recursing
Resources reference other resources within a tenant; for the largest tenant the reference table holds up to 2,000,000 nodes and 8,000,000 edges. Archiving a resource must archive everything reachable from it that nothing outside the set still references, refuse when a live external referrer exists, and terminate when references form cycles, which they legitimately do. Produce the archive order and the refusal list, targeting O(V+E). Say what stops the traversal crossing a tenant boundary, and why recursion is the wrong control structure at this size.
Approach
- Load the subgraph with the tenant predicate on both endpoints of the edge, not only on the side you started from. Scoping the left table alone is the classic cross-tenant leak: one mis-entered edge then pulls another tenant's resources into the traversal and, worse, into the archive.
- Traverse iteratively with an explicit stack. A 2,000,000-node graph can hold a chain deep enough to exhaust a native stack in the low tens of thousands of frames, and that failure is a process crash rather than an error you can return.
- Treat cycles as data rather than corruption: compute strongly connected components with Tarjan in O(V+E) using its own explicit stack, then condense. The condensation is a DAG, so a topological order over it gives the archive order, and every member of a component archives in one transaction because no order within a cycle is valid.
- Decide refusals with reverse edges. A candidate is archivable only if every in-edge originates inside the candidate set, so build the transpose or count in-degrees restricted to the visited set, and emit each blocked resource with the id of the external referrer, which is the only part of the answer an operator can act on.
Follow-up
- The graph is read in one query and the archive writes a minute later. What can change in between, and how do you make the write safe?
- The candidate set is 400,000 resources. Is that one transaction, and if not, what does a half-finished archive look like to a reader?
Merge partitioned event streams into one ordered feed with bounded lateness
The read-model service consumes 64 log partitions carrying about 4,000 events per second in total. Each partition is ordered within itself, but partitions drift by up to 30 seconds, and the activity feed must present a tenant's events in occurred_at order. Produce the merge. State its complexity, the buffer it requires in events and in bytes, what happens when one partition is idle, and what you do with an event that arrives after you have already emitted its position. Payloads average 1 KB.
Approach
- Merge with a min-heap over the 64 partition heads keyed on (occurred_at, event_id): O(log P) per event and O(n log P) overall. The tie-break on event_id is what makes the output deterministic when two partitions carry the same millisecond, which matters because the feed is paginated and a non-deterministic order reorders pages under the reader.
- Emitting the heap head is only correct once every partition has produced everything up to that timestamp, so the emit condition is a watermark: the minimum across partitions of the highest occurred_at seen, less the allowed lateness. Events are held until the watermark passes them, which is what turns individually ordered streams into a jointly ordered one.
- Size the buffer from the lateness rather than guessing: 4,000 events per second times 30 seconds is 120,000 buffered events, and at 1 KB each about 120 MB of heap. That number is the real price of the ordering guarantee and belongs in front of whoever asked for it.
- Handle the idle partition explicitly, because it fails the feed rather than corrupting it: a partition with no traffic never advances its own maximum, so the watermark freezes and output stops entirely. Either every partition emits a periodic idle marker carrying the broker's current time, or the watermark falls back to wall clock for a partition silent beyond a threshold.
Follow-up
- The lateness budget is raised to five minutes. What is the new buffer, and what besides memory changes?
- The consumer restarts. Where does it resume from, and what does the feed look like for the first 30 seconds?
What is the difference between inner, outer, and cross joins in SQL?
What is the difference between inner, outer, and cross joins in SQL?
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?
Can you explain the concept of normalization and why it is important for database design?
Can you explain the concept of normalization and why it is important for database design?
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?
Write a query to retrieve specific records from a table based on multiple conditions.
Write a query to retrieve specific records from a table based on multiple conditions.
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?
Explain the core principles of Object-Oriented Programming (OOP) and how you apply them in your projects.
Explain the core principles of Object-Oriented Programming (OOP) and how you apply them in your projects.
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 walk through a problem involving data structures such as lists, tuples, or arrays?
Can you walk through a problem involving data structures such as lists, tuples, or arrays?
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 are the differences between various collection types in your primary language?
What are the differences between various collection types in your primary language?
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 the process of designing a data model for a basic application.
Describe the process of designing a data model for a basic application.
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 approach debugging a piece of code that is failing in a production-like environment?
How do you approach debugging a piece of code that is failing in a production-like environment?
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?
Built from the rounds and topics PCS Global Tech candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the PCS Global Tech loop
- Write out the reported sequence: Initial Screening, Online Assessment, Technical Assessment, Final 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.
02Work SQL
- Spend the session on SQL, which PCS Global Tech candidates report being tested on.
- Write one worked example in SQL and time yourself on it.
Deliverable: One timed worked example in SQL.
03Work Database Concepts (DBMS)
- Spend the session on Database Concepts (DBMS), which PCS Global Tech candidates report being tested on.
- Write one worked example in Database Concepts (DBMS) and time yourself on it.
Deliverable: One timed worked example in Database Concepts (DBMS).
04Work SQL Query Basics
- Spend the session on SQL Query Basics, which PCS Global Tech candidates report being tested on.
- Write one worked example in SQL Query Basics and time yourself on it.
Deliverable: One timed worked example in SQL Query Basics.
05Answer out loud: Technical Foundations & Programming
- Answer aloud, timed: Explain the core principles of Object-Oriented Programming (OOP) and how you apply them in your projects.
- Answer aloud, timed: How do you handle memory management and basic algorithms in Python or Java?
Deliverable: Spoken answers to 2 reported Technical Foundations & Programming question(s), under time.
06Answer out loud: Database Management & SQL
- Answer aloud, timed: What is the difference between inner, outer, and cross joins in SQL?
- Answer aloud, timed: Can you explain the concept of normalization and why it is important for database design?
Deliverable: Spoken answers to 2 reported Database Management & SQL question(s), under time.
07Dry run for PCS Global Tech
- 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.
How do you handle memory management and basic algorithms in Python or Java?
How do you handle memory management and basic algorithms in Python or Java?
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 do you handle DML (Data Manipulation Language) commands in a relational database?
How do you handle DML (Data Manipulation Language) commands in a relational database?
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?
Estimate work you have never done and defend the range
You are asked to estimate a change you have never attempted: add a column to a 100-million-row table, populate it, move reads across, and drop the old shape. Give a range with the assumptions that generate it, including batch size, the signal your backfill throttles on, and wall-clock hours, and name the three unknowns that would move the number most. Then describe a real estimate you gave under comparable ignorance: how you expressed its uncertainty, what you committed to, and how wrong you turned out to be.
Approach
- Decompose into independently deployable steps before estimating anything: add the column nullable, write both shapes, backfill in batches, verify, move reads, stop writing the old shape, drop it. That is four deploys spread over days, and the calendar estimate is dominated by them rather than by the loop's runtime.
- Do the arithmetic aloud for the part that has arithmetic in it: batch size times number of batches times per-batch duration, at a write rate the primary can absorb alongside roughly 1.2k writes per second of production traffic. The loop is throttled by replication lag and lock waits, not by how fast it can issue statements.
- Price the schema step by its lock rather than its statement duration. In PostgreSQL an ALTER TABLE taking ACCESS EXCLUSIVE waits for every open transaction on that table while later queries queue behind it, so a millisecond change issued during a thirty-second analytics query stalls that table for thirty seconds. Adding a nullable column with a non-volatile default avoids a rewrite from version 11; a new index wants CREATE INDEX CONCURRENTLY, which cannot run inside a transaction block and leaves an invalid index behind if it fails.
- Express the answer as a range whose endpoints each trace to a stated assumption, then name the cheapest experiment that collapses it, which is almost always running one real batch against the real table and multiplying.
Follow-up
- How do you verify the backfill genuinely finished, given rows written by production traffic while it ran?
- Where does the backfill resume from after a worker is killed mid-batch, and what makes that resume point trustworthy?
- 01
How do you handle memory management and basic algorithms in Python or Java?
- 02
How do you handle DML (Data Manipulation Language) commands in a relational database?
- 03
You are asked to estimate a change you have never attempted: add a column to a 100-million-row table, populate it, move reads across, and drop the old shape. Give a range with the assumptions that generate it, including batch size, the signal your backfill throttles on, and wall-clock hours, and name the three unknowns that would move the number most. Then describe a real estimate you gave under comparable ignorance: how you expressed its uncertainty, what you committed to, and how wrong you turned out to be.
Is the technical interview very difficult?
The difficulty is generally described as manageable if you are well-prepared. The company often provides study materials—leverage them, as they are strong indicators of what you will be tested on.
PCS Global Tech Software Engineer candidate reports ↗What should I focus on for the online assessment?
Prioritize SQL basics and mathematical logic. Most candidates report that the assessment is heavily weighted toward database querying and data modeling.
PCS Global Tech Software Engineer candidate reports ↗Is the interview process entirely remote?
Yes, the vast majority of the process, including technical rounds and HR discussions, is conducted via video conferencing platforms. Ensure your environment is set up for a stable, professional video call.
PCS Global Tech Software Engineer candidate reports ↗What topics does PCS Global Tech test in interviews?
PCS Global Tech interviews most often cover SQL, SQL Query Writing, SQL (Structured Query Language), SQL Concepts, and Database Management Systems (DBMS). The exact emphasis depends on the specific role you apply for.
PCS Global Tech 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.
- 01PCS Global Tech 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
Explore related engineering environments and compare the preparation focus.
World Wide Technology Software Engineer Interview Guide
What World Wide Technology asks Software Engineer candidates, from reported rounds and questions.
W.W. Grainger Software Engineer Interview Guide
What W.W. Grainger asks Software Engineer candidates, from reported rounds and questions.
Vodafone Software Engineer Interview Guide
What Vodafone asks Software Engineer candidates, from reported rounds and questions.
Vertica Software Engineer Interview Guide
What Vertica asks Software Engineer candidates, from reported rounds and questions.