HCLTech Data Analyst Interview Questions (2026)

1. 1Online Assessment60 minMedium

   Aptitude, reasoning, and verbal sections plus technical MCQs (and coding for developer roles) used to shortlist for interviews.

2. 2Technical Interview40 minMedium

   Panel mixes programming fundamentals with OS, networking, and troubleshooting questions reflecting HCL's infra strength, plus project walkthroughs.

3. 3ER&D Domain Round45 minHard

   For engineering-services roles, a specialist round on embedded C/C++, protocols, or the specific product-engineering domain (automotive, medical, telecom).

4. 4Techno-Managerial Round35 minMedium

   For laterals, a manager checks incident/escalation handling, on-call and shift experience, and ownership on client deliverables.

5. 5HR Round25 minEasy

   Standard discussion covering shift and relocation flexibility, notice period or joining date, salary, and document verification.

1. Q1

   Write a SQL query to find duplicate customer records in HCLTech's credit-card client's spend-category dashboard. How would you decide which record survives?

   MediumSQL roundduplicate detectionHCLTech-specific

   Context:

   HCLTech credit-card client's spend-category dashboard

   How to answer:

   Use GROUP BY/HAVING or ROW_NUMBER over a business key, define survivorship rules, and push the fix upstream. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

2. Q2

   Using window functions, how would you add a 7-day rolling total and a rank within category to HCLTech's banking client's loan-portfolio reporting?

   MediumSQL roundwindow functionsHCLTech-specific

   Context:

   HCLTech banking client's loan-portfolio reporting

   How to answer:

   Contrast aggregate vs window behavior, frame clauses, and partition choices. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

3. Q3

   For HCLTech's retail client's daily sales dashboard, when would an INNER JOIN silently drop rows a LEFT JOIN would keep? Show the row counts you would check.

   MediumSQL roundjoinsHCLTech-specific

   Context:

   HCLTech retail client's daily sales dashboard

   How to answer:

   Explain join semantics with unmatched keys, and the count-before/count-after habit. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

4. Q4

   Your monthly GROUP BY summary for HCLTech's telecom client's churn reporting does not match the source system's total. How do you reconcile them?

   HardSQL roundaggregation and reconciliationHCLTech-specific

   Context:

   HCLTech telecom client's churn reporting

   How to answer:

   Compare grain, filters, timezone/date boundaries, late-arriving rows, and duplicates. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

5. Q5

   Which results change when key columns in HCLTech's insurance client's claims data mart contain NULLs — filters, joins, COUNT vs COUNT(col), averages?

   MediumSQL roundNULL handlingHCLTech-specific

   Context:

   HCLTech insurance client's claims data mart

   How to answer:

   Walk NULL semantics through WHERE, JOIN keys, aggregates, and COALESCE defaults. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

6. Q6

   After adding a join, revenue in HCLTech's e-commerce client's returns analysis doubled. Debug the query and prove the fix.

   HardSQL roundjoin fan-out debuggingHCLTech-specific

   Context:

   HCLTech e-commerce client's returns analysis

   How to answer:

   Detect one-to-many fan-out, pre-aggregate or dedupe the many side, verify with row counts. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

7. Q7

   When would you restructure a nested-subquery report for HCLTech's healthcare client's appointment no-show reporting into CTEs, and what does it cost?

   MediumSQL roundCTEs and subqueriesHCLTech-specific

   Context:

   HCLTech healthcare client's appointment no-show reporting

   How to answer:

   Readability, reuse, debugging layer by layer; note optimizer behavior differences. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

8. Q8

   Find the top 3 products per region by revenue in HCLTech's logistics client's delivery SLA tracking, handling ties explicitly.

   MediumSQL roundranking problemsHCLTech-specific

   Context:

   HCLTech logistics client's delivery SLA tracking

   How to answer:

   ROW_NUMBER vs RANK vs DENSE_RANK, and which tie behavior the business actually wants. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

9. Q9

   Your XLOOKUP against the master sheet in HCLTech's credit-card client's spend-category dashboard returns #N/A for valid IDs. What do you check?

   MediumExcel and BI roundlookupsHCLTech-specific

   Context:

   HCLTech credit-card client's spend-category dashboard

   How to answer:

   Trailing spaces, number-vs-text types, exact match mode, and TRIM/VALUE cleanup. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

10. Q10

    Build a pivot summary for HCLTech's banking client's loan-portfolio reporting: what goes in rows, values, and filters, and when does a pivot beat formulas?

    MediumExcel and BI roundpivot tablesHCLTech-specific

    Context:

    HCLTech banking client's loan-portfolio reporting

    How to answer:

    Structure the source as a flat table, choose aggregations, and know pivot refresh limits. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

11. Q11

    List the cleaning steps you would run on a raw extract for HCLTech's retail client's daily sales dashboard before any analysis.

    MediumExcel and BI rounddata cleaning in ExcelHCLTech-specific

    Context:

    HCLTech retail client's daily sales dashboard

    How to answer:

    Duplicates, blanks, types, date formats, merged cells, and a repeatable order of operations. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

12. Q12

    In Power BI, when does HCLTech's telecom client's churn reporting need a DAX measure instead of a calculated column?

    HardExcel and BI roundDAX measuresHCLTech-specific

    Context:

    HCLTech telecom client's churn reporting

    How to answer:

    Row context vs filter context, storage cost, and totals that only measures get right. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

13. Q13

    Design the Power BI model for HCLTech's insurance client's claims data mart: which tables are facts, which are dimensions, and why not one flat table?

    MediumExcel and BI rounddata modelingHCLTech-specific

    Context:

    HCLTech insurance client's claims data mart

    How to answer:

    Star schema, relationship directions, and what breaks when everything is one wide table. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

14. Q14

    The client says the HCLTech dashboard for e-commerce client's returns analysis takes a minute to load. How do you make it fast?

    MediumExcel and BI rounddashboard performanceHCLTech-specific

    Context:

    HCLTech e-commerce client's returns analysis

    How to answer:

    Reduce cardinality, trim visuals, pre-aggregate, and measure before optimizing. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

15. Q15

    Which KPIs go on the first screen of HCLTech's healthcare client's appointment no-show reporting, and what do you deliberately leave out?

    MediumExcel and BI rounddashboard designHCLTech-specific

    Context:

    HCLTech healthcare client's appointment no-show reporting

    How to answer:

    Lead with decisions the client makes weekly; park detail in drill-throughs. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

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