Top 30 Most Common sql server interview questions for 5 years experience You Should Prepare For

What are the top SQL Server interview questions for 5 years experience?

Direct answer: Employers expect a mix of core SQL querying, performance tuning, security, HA/DR knowledge, and procedural SQL — roughly the Top 30 questions span those domains.

• Core querying and problem-solving (joins, subqueries, window functions, aggregation, ranking).

• Performance and indexing (execution plans, missing-index DMVs, fragmentation).

• Programmability (stored procedures, functions, triggers, parameter sniffing).

• Security and best practices (authentication modes, roles, TDE, least privilege).

• High availability & disaster recovery (Always On, backups, log shipping).

• Database design and normalization (normal forms, keys, relationships).

• Expand:

For curated question collections see Simplilearn’s interview guide and CodeSignal’s breakdown for mid-to-senior SQL roles for real examples and sample answers.
Takeaway: Focus your prep across querying, performance, security, HA/DR, and programmability to cover what employers test at ~5 years experience.

How do I write a query to find the 3rd highest salary in SQL Server?

Direct answer: Use window functions (ROWNUMBER or DENSERANK) or a nested TOP query; window functions are the clearest and safest for ties.

Examples:

• Using ROW_NUMBER (distinct positions):

SELECT Salary
FROM (
  SELECT Salary, ROW_NUMBER() OVER (ORDER BY Salary DESC) AS rn
  FROM Employees
) t
WHERE rn = 3;

• Using DENSE_RANK (handles ties by rank):

SELECT Salary
FROM (
  SELECT Salary, DENSE_RANK() OVER (ORDER BY Salary DESC) AS rnk
  FROM Employees
) t
WHERE rnk = 3;

• Using TOP and subquery:

SELECT TOP 1 Salary
FROM (
  SELECT DISTINCT TOP 3 Salary
  FROM Employees
  ORDER BY Salary DESC
) AS t
ORDER BY Salary;

Insight: Use DENSERANK when tied salaries should share the same rank; ROWNUMBER when you need a strict position.
Takeaway: Prefer window functions for clarity, correctness with ties, and performance on modern SQL Server versions.

Explain the difference between correlated and nested subqueries — and when to use each

Direct answer: A nested subquery runs independently; a correlated subquery references the outer query and runs per outer row.

• Nested (independent) subquery:

• Executed once, result reused by outer query.

• Good for IN, EXISTS, scalar subqueries returning a single value.

• Correlated subquery:

• References outer query columns; executed for each row of the outer query.

• Useful for row-by-row comparisons (e.g., greatest value per group), but can be slower — often replaced with JOINs or window functions.

Expand:

SELECT e.EmployeeID, e.Salary
FROM Employees e
WHERE e.Salary > (SELECT AVG(Salary) FROM Employees WHERE DepartmentID = e.DepartmentID);

Example correlated:

Best practice: Replace correlated subqueries with joins or window functions where possible for scalability.
Takeaway: Understand cost and alternatives — use correlated queries only when logic requires per-row evaluation.

How can you optimize slow SQL Server queries?

Direct answer: Diagnose with the execution plan and DMVs, then apply targeted fixes: indexing, query rewrite, statistics, and configuration tweaks.

1. Capture actual execution plan and look for scans, expensive operators, and missing-index recommendations.

2. Use SET STATISTICS IO/TIME to measure I/O and CPU.

3. Ensure appropriate indexes (clustered, nonclustered, covering) and watch for over-indexing.

4. Update statistics frequently or enable automatic updates; consider filtered stats for skewed data.

5. Avoid non-SARGable predicates (no functions on indexed columns), excessive I/O from SELECT *, and unnecessary ORDER BY.

6. Consider query refactors: replace cursors with set-based logic, use window functions, or rewrite subqueries as joins.

7. Address parameter sniffing with OPTION (RECOMPILE) or parameterization strategies.

8. Use appropriate tempdb usage and monitor waits (e.g., PAGEIOLATCH, CXPACKET).

9. Steps:

Cite: For optimization patterns and deeper techniques, see CodeSignal’s performance question set and Edureka’s optimization tips.
Takeaway: Root-cause diagnosis via the plan and metrics beats guesswork — fix the hot spots, not symptoms.

What are common SQL Server constraints and how do they work?

Direct answer: Common constraints enforce data integrity: PRIMARY KEY, FOREIGN KEY, UNIQUE, CHECK, DEFAULT, and NOT NULL.

• PRIMARY KEY: Uniquely identifies rows; creates a unique index (clustered by default).

• FOREIGN KEY: Enforces referential integrity between tables; can cascade actions (ON DELETE/UPDATE).

• UNIQUE: Prevents duplicate values; allows NULLs (but only one NULL for some SQL dialects).

• CHECK: Enforces custom conditions (e.g., CHECK (Age >= 18)).

• DEFAULT: Supplies default values for columns when none provided.

• NOT NULL: Prevents NULLs in a column.

Explain:

CREATE TABLE Employees (
  EmployeeID INT PRIMARY KEY,
  ManagerID INT NULL,
  Salary DECIMAL(10,2) CHECK (Salary >= 0),
  CONSTRAINT FK_Manager FOREIGN KEY (ManagerID) REFERENCES Employees(EmployeeID)
);

Example:

Best practices: Prefer declarative constraints over application-side checks; they’re enforced at the engine level and improve data correctness and query optimizer assumptions.
Takeaway: Know how each constraint affects indexing, performance, and integrity — and how cascading rules behave.

How to create and execute stored procedures, functions, and triggers in SQL Server?

Direct answer: Use CREATE PROCEDURE/CREATE FUNCTION/CREATE TRIGGER syntax; know difference in usage, side effects, and execution context.

CREATE PROCEDURE usp_GetEmployeeById
  @EmployeeID INT
AS
BEGIN
  SET NOCOUNT ON;
  SELECT * FROM Employees WHERE EmployeeID = @EmployeeID;
END;
-- Execute:
EXEC usp_GetEmployeeById @EmployeeID = 123;

Stored procedure example:

CREATE FUNCTION dbo.ufn_GetTaxRate(@Salary DECIMAL(10,2))
RETURNS DECIMAL(5,2)
AS
BEGIN
  DECLARE @rate DECIMAL(5,2) = CASE WHEN @Salary > 100000 THEN 30 ELSE 20 END;
  RETURN @rate;
END;

Scalar function example:

CREATE TRIGGER trg_AuditEmployeeUpdate
ON Employees
AFTER UPDATE
AS
BEGIN
  INSERT INTO EmployeeAudit(EmployeeID, ChangedAt) SELECT EmployeeID, GETDATE() FROM inserted;
END;

Trigger example:

• Stored procedures: support transactions, multiple result sets, and can perform DML — used for business logic.

• Functions: can be deterministic/inline and used in SELECT; avoid multi-statement scalar functions for performance issues.

• Triggers: fire on DML and can be used for auditing but can introduce hidden performance costs if heavy.

Differences and tips:

Debugging and optimization: Use SQL Server Profiler/Extended Events, SET STATISTICS, and consider replacing scalar UDFs with inline table-valued functions or APPLY for performance. See InterviewBit and Edureka for sample patterns.
Takeaway: Master syntax and when to use each object; know performance trade-offs (especially UDFs and triggers).

What performance tuning and indexing best practices should a mid-level candidate know?

Direct answer: Understand index types, execution plans, statistics, fragmentation, and when to use covering indexes or index maintenance.

• Choose clustered index on column(s) used for range queries or unique IDs; keep clustered key narrow.

• Create nonclustered and covering indexes to satisfy queries without lookups.

• Use INCLUDE for non-key columns to avoid lookups for frequently selected columns.

• Monitor fragmentation (sys.dmdbindexphysicalstats) and rebuild/reorganize as needed.

• Check index usage with sys.dmdbindexusagestats and remove unused indexes.

• Use filtered indexes for selective predicates; use columnstore indexes for large analytic workloads.

• Keep statistics accurate (sys.stats) and use proper auto-update settings; consider sample rates for huge tables.

• Read execution plans (actual) for operator costs, missing index hints, and parameter sniffing signs.

Key practices:

Reference: CodeSignal and UPES Online cover advanced tuning and HA considerations for experienced candidates.
Takeaway: Effective indexing combines schema design, workload analysis, and proactive maintenance — learn to read plans and act accordingly.

How do you secure SQL Server and manage authentication and encryption?

Direct answer: Use principle of least privilege, prefer Windows Authentication, harden logins/roles, enable encryption (TDE/Always Encrypted), and audit access.

• Authentication: Prefer integrated Windows Authentication for domain-joined environments; use contained users for cloud scenarios.

• Authorization: Grant minimal permissions; use fixed server/DB roles sparingly and create custom roles for tasks.

• Encryption:

• TDE (Transparent Data Encryption) encrypts data-at-rest.

• Always Encrypted protects sensitive columns so keys stay client-side.

• Column-level encryption and symmetric/asymmetric keys for fine-grained use.

• Auditing and monitoring: Use SQL Server Audit or Extended Events for login failures, permission changes, and DDL/DML auditing.

• Network security: Force encrypted connections (TLS), restrict surface area, and use firewall rules.

• Patch and baseline: Keep SQL Server patched, and enforce secure baseline configuration.

Practical steps:

Cite: Simplilearn’s and CodeSignal’s security primers outline authentication modes and encryption features.
Takeaway: Security is layered — authentication, authorization, encryption, and auditing together reduce risk and are frequent interview topics.

What is Always On Availability Groups and what backup/DR strategies should I know?

Direct answer: Always On Availability Groups provide high-availability and read-scale by replicating databases across replicas; you should also understand full/differential/log backups and recovery models.

• Always On AG:

• Supports primary and multiple secondary replicas, readable secondaries, and automatic failover (with Windows Server Failover Clustering).

• Requires enterprise edition for some features (note licensing differences across SQL Server versions).

• Backup types:

• Full backups capture entire DB.

• Differential backups capture changes since last full.

• Transaction log backups enable point-in-time recovery under FULL recovery model.

• DR strategies:

• Log shipping (asynchronous), database mirroring (legacy), and Always On AGs for modern HA/DR.

• Offsite backups, geo-redundant storage, and tested restore procedures are mandatory.

• Consider RPO (Recovery Point Objective) and RTO (Recovery Time Objective) to choose sync vs async replication.

Overview:

Reference: CodeSignal and UPES Online provide higher-level HA/DR question sets that commonly appear in senior DBA interviews.
Takeaway: Know both architecture and operational steps — backups, restores, and failover procedures are interview essentials.

How do you design normalized databases and when should you denormalize?

Direct answer: Apply normal forms to remove redundancy and enforce integrity; denormalize selectively for performance or reporting needs.

• Normalization:

• 1NF: atomic values.

• 2NF: remove partial dependencies.

• 3NF: remove transitive dependencies.

• Higher forms (BCNF, 4NF) for specialized normalization.

• Keys and relationships:

• Use surrogate keys (IDENTITY/GUID) vs natural keys depending on stability and meaning.

• Enforce relationship integrity with foreign keys.

• Denormalization:

• Use when query performance demands fewer joins, for read-heavy analytic workloads, or to support caching strategies.

• Balance increased storage, update complexity, and risk of data anomalies.

• Modeling tips:

• Use ER diagrams, document constraints and business rules, and consider indexing strategy as part of schema design.

Guidelines:

See UPES Online and GeeksforGeeks for examples and common normalization interview prompts.
Takeaway: Demonstrate both theory (normal forms) and practical trade-offs (when denormalization is appropriate) in interviews.

What are common pitfalls with stored procedures, functions, and triggers — and how to avoid them?

Direct answer: Common issues include scalar UDF performance costs, hidden trigger side-effects, long-running transactions, and poor parameter handling — avoid by using set-based logic and monitoring.

• Scalar UDFs: can cause row-by-row processing; replace with inline table-valued functions or rewrite logic using APPLY and window functions.

• Multi-statement functions: avoid where possible; they often disable plan optimizations.

• Triggers: can introduce cascading performance hits — keep them minimal and asynchronous where possible (use audit tables with minimal logic).

• Long transactions: increase lock contention and log growth; keep transactions short.

• Parameter sniffing: mitigate with OPTION (RECOMPILE), optimized plan guides, or use local variables carefully.

Pitfalls and fixes:

Reference: InterviewBit and Edureka provide practical guidance and patterns to spot these pitfalls in interviews.
Takeaway: Be ready to explain how you’d detect and fix hidden costs in procedural code.

How should you prepare for behavioral and systems-design questions around SQL Server roles?

Direct answer: Combine technical answers with specific examples (STAR or CAR format): describe Situation, Task, Actions, and Results.

• Behavioral: Prepare 4–6 stories about performance tuning, incident response, migration, or cross-team collaboration. Quantify results (e.g., reduced query time from 60s to 2s).

• Systems design: Be ready to design for scale — partitioning, read replicas, caching, backup policies, monitoring and alerting.

• Demonstrate trade-offs: When asked about HA choices, discuss RPO/RTO trade-offs and cost implications.

Preparation tips:

Cite: Many interview preparation resources emphasize structured answers; practicing STAR helps you communicate clearly and concisely.
Takeaway: Use structured stories and quantifiable outcomes to show both technical skill and impact.

How Verve AI Interview Copilot Can Help You With This

Verve AI offers a quiet, real-time co-pilot that analyzes interview prompts and context, suggests structured answers (STAR/CAR), and cues concise follow-ups so you stay focused under pressure. As you answer, Verve AI can recommend precise SQL snippets, highlight performance-tuning talking points, and remind you to quantify outcomes — helping with phrasing and calm delivery. Use Verve AI Interview Copilot during mock or live interviews to keep responses structured, accurate, and interview-ready.

What Are the Most Common Questions About This Topic

Q: Can Verve AI help with behavioral interviews?
A: Yes — it prompts STAR/CAR structure, suggests examples, and keeps your answers concise and measurable.

Q: How do I practice SQL queries for interviews?
A: Solve real problems, code on sample schemas, use window functions, and time yourself for speed and accuracy.

Q: What should I emphasize for a 5-year SQL role?
A: Performance tuning, indexing, stored procedures, HA/DR, security, and measurable impact on systems.

Q: How technical should my answers be in interviews?
A: Tailor depth to interviewer signals: be concise, offer to dive deeper, and back claims with metrics or a plan.

Q: Are online guides enough to prepare?
A: They’re valuable for breadth; combine guides with hands-on practice, execution plans, and live mock interviews.

(Note: Each answer above is designed to be compact yet informative for rapid reading.)

Conclusion

Recap: For a 5-year SQL Server role, prepare across core querying, performance tuning, security, HA/DR, database design, and programmability. Use window functions and execution plans as your go-to tools, apply indexing and statistics wisely, and practice structured behavioral answers that showcase impact. Preparation and structure build confidence — and the right tools can help you deliver under pressure. Try Verve AI Interview Copilot to feel confident and prepared for every interview.