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REQUIREMENT_ID_112 β€’ 3-DAY_ACTIVE_POLICY

Data Analyst

Company
Company Wipro
Type
Opportunity Type Full-Time Job
Salary
Stipend / Salary 6 LPA - 9 LPA
Location
Location Gurugram, Haryana
Posted Date
Posted Date Today
Advanced SQL ETL PLX scripts PLX dashboards Looker Studio Google Workspace Data Modeling Analytical Thinking Python JavaScript VBA
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Wipro Placement Papers – Data Analyst Open Resource β†—
Compilation of past placement papers that help you understand the type of questions Wipro asks for data analyst roles.
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Wipro Recruitment Process Experiences Open Resource β†—
First‑hand experiences of candidates detailing each interview round, useful for preparation strategy.
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Data Analyst Interview Guide for Wipro Open Resource β†—
Targeted guide covering core topics, sample questions and tips specific to Wipro's data analyst interview.
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Algorithm Practice Problems Open Resource β†—
Extensive problem set to sharpen coding and problem‑solving skills, essential for technical rounds.

Any graduate (Engineering / Computer Science / Mathematics / Statistics preferred). Minimum 60% aggregate (or CGPA 6.0/10). 4–6 years of relevant experience in backend data engineering or analytics. No active backlogs. Strong communication skills and ability to work in a structured, process‑driven environment.

1
Round 1: Online assessment (aptitude + basic SQL)
2
Round 2: Technical interview (SQL, ETL design, PLX, case study)
3
Round 3: HR interview (fit, motivation, compensation discussion)
Wipro Limited is one of India’s largest technology services and consulting firms, with a heritage of more than three decades in delivering end‑to‑end digital transformation solutions. Operating in over 65 countries and employing more than 230,000 professionals, Wipro helps enterprises across industries modernise their operations, adopt cloud, harness data, and build sustainable business models. The company’s culture is built around purpose, inclusivity and continuous reinvention, encouraging employees to experiment, learn and grow. The Data Analyst role in Gurugram sits within the Data Analytics family and reports to the Assistant Manager level. It is a core backend data engineering and analytics position that focuses on designing, building, and maintaining robust data pipelines, transforming raw data into analytical datasets, and delivering actionable insights through dashboards. The role works closely with cross‑functional stakeholders, translating business questions into scalable data solutions that drive decision‑making. Key responsibilities include: 1. Design, develop, and maintain SQL‑based ETL pipelines that ingest, cleanse, and aggregate large volumes of structured data. 2. Write advanced Google‑SQL/BigQuery queries involving complex joins, CTEs, window functions, and performance tuning. 3. Create and optimise PLX scripts for automated backend processing and data orchestration. 4. Build and maintain PLX dashboards that provide real‑time operational visibility. 5. Develop Looker Studio reports and visualisations aligned with business metrics. 6. Collaborate with product, operations and finance teams to understand data requirements and deliver reliable datasets. 7. Perform deep‑dive analysis to uncover trends, anomalies and growth opportunities. 8. Ensure data quality, governance and documentation across all pipelines. 9. Participate in code reviews, data modelling discussions and continuous improvement initiatives. 10. Mentor junior analysts on best practices in SQL, ETL design and dashboarding. Technical stack: Google BigQuery, Advanced SQL, PLX scripting, Looker Studio, Google Workspace (Docs, Sheets, Slides), optional Python/JavaScript/VBA for automation, and familiarity with data modelling concepts. Growth path: Successful analysts can progress to Senior Data Analyst, Data Engineering Lead, or Manager – Data Analytics, with exposure to strategic projects, client‑facing responsibilities and opportunities to specialise in emerging domains such as AI‑driven analytics. Why join Wipro? The company offers a stable platform backed by global clients, a structured learning ecosystem (Wipro Learning Academy), and a culture that rewards innovation. Employees benefit from flexible work arrangements, competitive compensation, and a clear roadmap for career advancement, making it an ideal place for data professionals eager to make an impact at scale.

Wipro 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 🎯
Wipro Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Wipro 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 (Advanced SQL, ETL, PLX scripts, PLX dashboards, Looker Studio, Google Workspace, Data Modeling, Analytical Thinking, Python, JavaScript, VBA) & 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
Wipro 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 Wipro as a Data Analyst?
Preparation Tip: Highlight Wipro's market reputation, recent tech innovations, and how your skills in Advanced 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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