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Dentsu Tech Hackathon

Company
Company Hackerearth
Type
Opportunity Type Internship
Salary
Stipend / Salary Rs 15,000 per month
Location
Location Mumbai/Pune, India
Posted Date
Posted Date Today
Python SQL Data Modeling ETL Problem Solving Analytical Thinking Communication Team Collaboration Basic Cloud Concepts
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Aptitude Practice Questions Open Resource ↗
Curated MCQs and logical reasoning problems to sharpen quantitative and verbal skills required for the screening round.
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Company Interview Corner Resources Open Resource ↗
Compilation of interview experiences, common technical questions, and preparation tips for tech internships at leading firms.
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Comprehensive Preparation Guides Open Resource ↗
Step‑by‑step guides covering programming fundamentals, data structures, and SQL concepts essential for the hackathon challenges.
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Algorithm Problem Set Open Resource ↗
Extensive collection of coding problems to practice coding speed, accuracy, and problem‑solving techniques for the programming section.

Graduates or final‑year students of B.Tech, B.E., B.Sc., MCA, or related fields; minimum 60% aggregate or CGPA 6.0/10; no active backlogs at the time of application; batch year 2025‑2027 (preferably 2026); strong foundation in programming, data handling, and analytical thinking; willingness to work on‑site in Mumbai or Pune for the internship period.

1
Round 1: Tech Round – Screening (15 MCQs, 2 Programming Questions, 1 SQL Question)
2
Round 2: Approach Deck Submission (7–10 slides)
3
Round 3: Interviews (Technical Deep‑Dive and HR)
4
Round 4: Build Phase (2–3 month in‑office internship)
Dentsu is a global leader in communications, media, and digital marketing, with a strong footprint in India. With over a century of experience, Dentsu helps brands transform their business through data‑driven insights, creative storytelling, and cutting‑edge technology. The company’s Indian operations, headquartered in Mumbai and Pune, focus on delivering integrated campaigns that blend traditional media with advanced programmatic solutions, AI‑powered analytics, and innovative tech tools. Dentsu’s culture encourages curiosity, collaboration, and continuous learning, making it an ideal place for fresh talent to grow. The Dentsu Tech Hackathon 2026 is a unique, real‑world challenge designed to identify and nurture emerging technologists. Participants will work on a "Campaign Intelligence Workflow" problem, showcasing their ability to design, develop, and automate solutions that can be directly applied to Dentsu’s client‑facing platforms. Successful candidates will be offered a three‑month, in‑office internship where they will turn their prototype into a production‑ready tool, gaining hands‑on experience with industry‑grade data pipelines, automation scripts, and analytics dashboards. **Key Responsibilities** 1. Analyze the campaign intelligence workflow and identify automation opportunities. 2. Design data models and schemas to support real‑time reporting. 3. Develop end‑to‑end pipelines using Python, SQL, and cloud services. 4. Build interactive dashboards or visualisations for stakeholder consumption. 5. Write clean, modular code adhering to Dentsu’s coding standards. 6. Participate in regular checkpoint demos and incorporate feedback. 7. Document solution architecture, data flow, and deployment steps. 8. Collaborate with cross‑functional teams including media planners, data scientists, and product managers. 9. Conduct testing, performance tuning, and debugging of the prototype. 10. Present the final solution to senior leadership at the end of the build phase. **Tech Stack**: Python, Pandas, SQL, PostgreSQL/MySQL, AWS (S3, Lambda, Glue), Tableau/PowerBI, Git, Docker. **Growth Path**: Interns who excel may receive a full‑time offer as Automation Intern, Data Intern, or Tech Tools Intern, with clear progression to Analyst, Associate, and Manager roles within Dentsu’s technology practice. **Why Join**: Working at Dentsu provides exposure to world‑class advertising campaigns, mentorship from industry veterans, and the chance to solve problems that impact millions of consumers. The hackathon format accelerates learning, offers a tangible portfolio piece, and opens doors to a rewarding career in ad‑tech. Overall, this hackathon is not just a competition—it is a gateway to a structured internship that blends creativity with technical rigor, positioning participants for long‑term success in the fast‑evolving digital marketing ecosystem.

Hackerearth — 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 🎯
Hackerearth Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Hackerearth 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 (Python, SQL, Data Modeling, ETL, Problem Solving, Analytical Thinking, Communication, Team Collaboration, Basic Cloud Concepts) & 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
Hackerearth 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 Hackerearth as a Dentsu Tech Hackathon?
Preparation Tip: Highlight Hackerearth's market reputation, recent tech innovations, and how your skills in Python 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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