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REQUIREMENT_ID_1344 • 3-DAY_ACTIVE_POLICY JD

Nasdaq Campus Program

Company
Company Nasdaq
Type
Opportunity Type Internship
Salary
Stipend / Salary ₹50,000 per month (stipend)
Location
Location Bengaluru, Karnataka, India
Posted Date
Posted Date Yesterday
Apply on Official Website ↗
Programming fundamentals Data Structures & Algorithms SQL Database fundamentals Communication Teamwork Problem Solving Analytical Thinking
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Aptitude Practice Questions Open Resource ↗
Curated aptitude problems to sharpen quantitative and logical reasoning essential for the online assessment.
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Technical Interview Preparation Guide Open Resource ↗
Comprehensive guide covering coding patterns, data structures, and system design topics frequently asked at Nasdaq.
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Comprehensive Interview Prep Resource Open Resource ↗
A collection of interview experiences, tips, and mock questions to help candidates build confidence.
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Algorithm Problem Set Open Resource ↗
Extensive set of coding problems to practice algorithmic thinking and improve speed for the assessment round.

Graduating in 2027 with a Bachelor's degree in Computer Science, Information Technology, Electronics & Communication, or related engineering streams; minimum CGPA/percentage of 6.5/70%; no active backlogs at the time of joining; strong analytical and problem‑solving abilities; eligibility to work in India without sponsorship.

1
Round 1: Online Assessment (coding & aptitude)
2
Round 2: Technical Interview (DSA, system design, role‑specific questions)
3
Round 3: HR Interview (fit, motivation, cultural alignment)
Nasdaq is a world‑leading global financial technology company that operates the world’s premier stock exchange and provides market data, analytics, and trading solutions to investors, issuers, and financial institutions. With a strong presence in more than 50 countries, Nasdaq has built a reputation for innovation, transparency, and reliability in the capital markets. The company’s technology arm focuses on building cutting‑edge platforms that power real‑time trading, data distribution, and cloud‑based services, making it an attractive destination for fresh engineering talent. The Nasdaq Campus Program – 2027 is designed for graduating students who are eager to start their professional journey in a fast‑paced, technology‑driven environment. Selected candidates will join a structured onboarding track that blends classroom learning, hands‑on projects, and mentorship from senior engineers. Participants will work on real‑world problems ranging from building low‑latency trading engines to developing data pipelines and visualisation tools for market analytics. Key responsibilities include: 1. Collaborate with cross‑functional teams to design, develop, and test software components for trading and data platforms. 2. Write clean, efficient, and maintainable code following industry best practices. 3. Participate in code reviews and contribute to continuous improvement of development processes. 4. Analyse large data sets, create SQL queries, and support data‑driven decision making. 5. Debug and resolve production issues with a focus on minimizing downtime. 6. Document technical specifications, architecture diagrams, and user guides. 7. Engage in agile ceremonies such as sprint planning, stand‑ups, and retrospectives. 8. Stay updated with emerging technologies like cloud services, micro‑services, and AI/ML, and propose innovative solutions. 9. Contribute to internal tools that enhance developer productivity. 10. Participate in hackathons and internal innovation challenges. The typical tech stack includes Java, Python, C++, SQL/NoSQL databases, RESTful APIs, Docker, Kubernetes, and cloud platforms such as AWS or Azure. The program offers a clear growth path: after successful completion, participants may be offered full‑time roles, with opportunities to rotate across product, infrastructure, and data teams, eventually moving into senior engineering or product leadership positions. Why join Nasdaq? The brand offers unparalleled exposure to the financial markets, a culture that encourages continuous learning, and a collaborative environment where fresh ideas are valued. The stipend of ₹50,000 per month provides financial support while you gain experience that is highly regarded across the tech industry.

Nasdaq — Data Analytics & SQL Interview Guide

Previously asked questions, exam syllabus, coding benchmarks & round strategy.

APTITUDE & LOGIC 📖
Aptitude Practice Questions & Online Mock Tests

Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.

Open Resource ↗
COMPANY GUIDE 🎯
Nasdaq Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Nasdaq and off-campus tech roles.

Open Resource ↗
MOCK TESTS & PAPERS 📝
Comprehensive Interview Prep Resources & Syllabus

Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.

Open Resource ↗
CODING PRACTICE 💻
Algorithm and Data Structure Problem Set

Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.

Open Resource ↗
Round 1: Online Assessment (OA)
Aptitude, Quantitative Logic & 2 Coding Problems
Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1
Core Tech Stack (Programming fundamentals, Data Structures & Algorithms, SQL, Database fundamentals, Communication, Teamwork, Problem Solving, Analytical Thinking) & Live Code Tracing
Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving
Database Schemas, APIs & Architecture Basics
Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion
Nasdaq Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
What is the difference between WHERE and HAVING clauses in SQL? Answer ▼
Model Answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer ▼
Model Answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer ▼
Model Answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer ▼
Model Answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer ▼
Model Answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Why do you want to join Nasdaq as a Nasdaq Campus Program?
Preparation Tip: Highlight Nasdaq's market reputation, recent tech innovations, and how your skills in Programming fundamentals directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Preparation Tip: Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Preparation Tip: Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.

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