Tech Mahindra Data Analyst Interview Questions (2026)

1. 1Online Assessment (English + Aptitude + Coding)60 minMedium

   Timed test where English grammar/comprehension and a written email or essay task carry unusual weight, alongside quantitative aptitude and basic coding questions.

2. 2Technical Interview40 minMedium

   Panel covers programming and CS fundamentals, projects, and — for network-aligned roles — telecom basics like the OSI stack and call flows.

3. 3Telecom Domain Round45 minHard

   For experienced OSS/BSS, 5G, or network-engineering hires, a specialist round on charging/billing flows, provisioning, network protocols, or RAN/core architecture.

4. 4Managerial Round30 minMedium

   A delivery manager evaluates client-communication maturity, shift and travel flexibility, and handling of escalations on live telecom accounts.

5. 5HR Round25 minEasy

   Closing discussion on communication, relocation/shift willingness, compensation, and culture fit framed around the Mahindra Rise philosophy.

1. Q1

   Write a SQL query to find duplicate customer records in Tech Mahindra's retail client's daily sales dashboard. How would you decide which record survives?

   MediumSQL roundduplicate detectionTech Mahindra-specific

   Context: Tech Mahindra retail client's daily sales 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 Tech Mahindra's telecom client's churn reporting?

   MediumSQL roundwindow functionsTech Mahindra-specific

   Context: Tech Mahindra telecom client's churn 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 Tech Mahindra's insurance client's claims data mart, when would an INNER JOIN silently drop rows a LEFT JOIN would keep? Show the row counts you would check.

   MediumSQL roundjoinsTech Mahindra-specific

   Context: Tech Mahindra insurance client's claims data mart

   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 Tech Mahindra's e-commerce client's returns analysis does not match the source system's total. How do you reconcile them?

   HardSQL roundaggregation and reconciliationTech Mahindra-specific

   Context: Tech Mahindra e-commerce client's returns analysis

   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 Tech Mahindra's healthcare client's appointment no-show reporting contain NULLs — filters, joins, COUNT vs COUNT(col), averages?

   MediumSQL roundNULL handlingTech Mahindra-specific

   Context: Tech Mahindra healthcare client's appointment no-show reporting

   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 Tech Mahindra's logistics client's delivery SLA tracking doubled. Debug the query and prove the fix.

   HardSQL roundjoin fan-out debuggingTech Mahindra-specific

   Context: Tech Mahindra logistics client's delivery SLA tracking

   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 Tech Mahindra's credit-card client's spend-category dashboard into CTEs, and what does it cost?

   MediumSQL roundCTEs and subqueriesTech Mahindra-specific

   Context: Tech Mahindra credit-card client's spend-category dashboard

   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 Tech Mahindra's banking client's loan-portfolio reporting, handling ties explicitly.

   MediumSQL roundranking problemsTech Mahindra-specific

   Context: Tech Mahindra banking client's loan-portfolio reporting

   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 Tech Mahindra's retail client's daily sales dashboard returns #N/A for valid IDs. What do you check?

   MediumExcel and BI roundlookupsTech Mahindra-specific

   Context: Tech Mahindra retail client's daily sales 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 Tech Mahindra's telecom client's churn reporting: what goes in rows, values, and filters, and when does a pivot beat formulas?

    MediumExcel and BI roundpivot tablesTech Mahindra-specific

    Context: Tech Mahindra telecom client's churn 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 Tech Mahindra's insurance client's claims data mart before any analysis.

    MediumExcel and BI rounddata cleaning in ExcelTech Mahindra-specific

    Context: Tech Mahindra insurance client's claims data mart

    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 Tech Mahindra's e-commerce client's returns analysis need a DAX measure instead of a calculated column?

    HardExcel and BI roundDAX measuresTech Mahindra-specific

    Context: Tech Mahindra e-commerce client's returns analysis

    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 Tech Mahindra's healthcare client's appointment no-show reporting: which tables are facts, which are dimensions, and why not one flat table?

    MediumExcel and BI rounddata modelingTech Mahindra-specific

    Context: Tech Mahindra healthcare client's appointment no-show reporting

    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 Tech Mahindra dashboard for logistics client's delivery SLA tracking takes a minute to load. How do you make it fast?

    MediumExcel and BI rounddashboard performanceTech Mahindra-specific

    Context: Tech Mahindra logistics client's delivery SLA tracking

    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 Tech Mahindra's credit-card client's spend-category dashboard, and what do you deliberately leave out?

    MediumExcel and BI rounddashboard designTech Mahindra-specific

    Context: Tech Mahindra credit-card client's spend-category dashboard

    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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Clear the aptitude and coding test; revise fundamentals and projects; prepare HR questions

Indicative Data Analyst pay in India: ~₹6–22 LPA (role-level range, not a Tech Mahindra-specific figure).

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