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REQUIREMENT_ID_174 β€’ 3-DAY_ACTIVE_POLICY

Data Analyst

Company
Company Capgemini
Type
Opportunity Type Internship
Salary
Stipend / Salary β‚Ή5 LPA
Location
Location Bangalore, India
Posted Date
Posted Date Yesterday
SQL Python Data Visualization Power BI Tableau Excel Statistical Analysis Problem Solving Communication Team Collaboration
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Capgemini Placement Papers Open Resource β†—
A collection of previous placement papers that help you practice the type of questions asked in Capgemini recruitment.
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Capgemini Recruitment Process Insights Open Resource β†—
Detailed experiences from candidates covering each interview round, useful for setting expectations.
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Capgemini Interview Preparation Guide Open Resource β†—
Comprehensive guide with tips, sample questions and recommended study topics for Capgemini interviews.
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Algorithm Practice Problems Open Resource β†—
A curated set of coding problems to sharpen problem‑solving skills required for technical rounds.

Graduation (B.Tech/B.E/MCA/BS) in Computer Science, Information Technology, Electronics, Statistics or related fields; Minimum 60% aggregate (or CGPA 6.0/10); No active backlogs at the time of application; Batch years 2020‑2026 accepted; Strong analytical mindset and good communication skills.

1
Round 1: Online Aptitude & Technical MCQ
2
Round 2: Technical Interview (SQL, Python, case study)
3
Round 3: HR Interview (fitment, motivations, salary expectations)
Capgemini is a global leader in consulting, technology services and digital transformation. With a presence in over 50 countries and a strong foothold in India, the company helps Fortune 500 clients re‑imagine their businesses through innovative solutions. Capgemini Engineering, the technology‑focused arm of the group, works on cutting‑edge software, product development and data‑driven projects for industries ranging from automotive to finance. The firm is known for its collaborative culture, continuous learning programs and a clear career progression path for fresh talent and experienced professionals alike. The Data Analyst role at Capgemini Engineering in Bangalore is a permanent position that sits at the intersection of business and technology. As a Data Analyst, you will be responsible for turning raw data into actionable insights that drive strategic decisions for clients and internal stakeholders. You will work closely with senior engineers, product managers and domain experts to understand data requirements, design analytical solutions and communicate findings in a clear, visual format. **Key Responsibilities** 1. Gather, clean and preprocess structured and unstructured data from multiple sources. 2. Perform exploratory data analysis to identify trends, patterns and anomalies. 3. Develop and maintain dashboards and reports using Power BI, Tableau or similar visualization tools. 4. Write efficient SQL queries and Python scripts for data extraction, transformation and loading (ETL). 5. Conduct statistical analysis and predictive modelling to support business cases. 6. Collaborate with cross‑functional teams to translate business problems into analytical solutions. 7. Document data pipelines, methodologies and findings for reproducibility. 8. Ensure data quality, governance and compliance with security standards. 9. Participate in agile ceremonies, provide status updates and contribute to sprint planning. 10. Mentor junior analysts and share best practices across the team. **Tech Stack**: SQL, Python (pandas, numpy), R (optional), Power BI, Tableau, Excel, Git, basic knowledge of Hadoop/Spark, REST APIs for data ingestion. **Growth Path**: Starting as a Data Analyst, you can progress to Senior Analyst, Data Scientist, Analytics Lead and eventually to Manager or Director of Analytics, with opportunities to move across domains and geographies within the Capgemini network. **Why Join Capgemini**: Working at Capgemini gives you exposure to global clients, state‑of‑the‑art tools and a culture that rewards curiosity and continuous upskilling. The company invests heavily in learning platforms, certifications and mentorship programs, ensuring that you stay ahead in the rapidly evolving data landscape. Moreover, the collaborative environment and emphasis on work‑life balance make it an ideal place for fresh graduates and early‑career professionals to launch a rewarding analytics career.

Capgemini β€” Data Analytics & SQL Interview Guide

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

APTITUDE & LOGIC πŸ“–
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 β†—
COMPANY GUIDE 🎯
Capgemini Interview Preparation Corner

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

Open Resource β†—
MOCK TESTS & PAPERS πŸ“
Comprehensive Interview Prep Resources & Syllabus

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

Open Resource β†—
CODING PRACTICE πŸ’»
Algorithm and Data Structure Problem Set

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

Open Resource β†—
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 (SQL, Python, Data Visualization, Power BI, Tableau, Excel, Statistical Analysis, Problem Solving, Communication, Team Collaboration) & 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
Capgemini 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 β–Ό
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 β–Ό
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 β–Ό
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 β–Ό
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 β–Ό
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 Capgemini as a Data Analyst?
Preparation Tip: Highlight Capgemini's market reputation, recent tech innovations, and how your skills in SQL 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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