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REQUIREMENT_ID_1467 β€’ 3-DAY_ACTIVE_POLICY

Data Analyst

Company
Company Barclays
Type
Opportunity Type Internship
Salary
Stipend / Salary 6 LPA - 9 LPA
Location
Location Gurugram, India
Posted Date
Posted Date Yesterday
SQL Python R Data Visualization Statistics Excel Problem Solving Communication Business Acumen
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Aptitude Practice Questions Open Resource β†—
Curated quantitative and logical reasoning problems to sharpen the analytical skills needed for the online assessment at Barclays.
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Company Interview Preparation Guide Open Resource β†—
Comprehensive guide covering typical interview formats, sample questions, and tips specific to banking and analytics roles like the one at Barclays.
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Comprehensive Interview Prep Resources Open Resource β†—
A collection of interview experiences, mock tests, and subject‑wise notes to help candidates confidently tackle technical rounds for data analyst positions.
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Algorithm & Data Structure Problem Set Open Resource β†—
Extensive set of coding problems to practice Python/SQL based algorithmic challenges often asked in technical interviews for analytics roles.

Graduates (B.Tech/B.E., B.Sc., B.Com, BBA) in Computer Science, Statistics, Mathematics, Economics, or related fields; Minimum 60% aggregate or CGPA 6.0/10; Batch 2024‑2026; No active backlogs at the time of joining; Strong analytical mindset and willingness to learn.

1
Round 1: Online Aptitude & Logical Reasoning Test
2
Round 2: Technical Interview (SQL/Python & Case Study)
3
Round 3: HR Interview (fitment, motivation, cultural fit)
Barclays is a global financial services powerhouse with a legacy spanning over three centuries. In India, the bank has built a strong presence across retail banking, corporate banking, and wealth management, offering innovative solutions to millions of customers. The organization prides itself on a culture of inclusion, continuous learning, and a commitment to sustainability, making it an attractive destination for fresh talent eager to make an impact in the financial sector. As a Data Analyst in the Digital, Data & Analytics business area, you will be part of a high‑performing team that transforms raw data into actionable insights for business decision‑making. You will work closely with product managers, engineers, and senior analysts to design, develop, and maintain analytical solutions that drive performance across Barclays’ digital platforms. This role offers exposure to cutting‑edge analytics tools, a collaborative environment, and a clear growth trajectory toward senior analytical and data‑science positions. Key Responsibilities: 1. Collect, clean, and validate large data sets from multiple internal and external sources. 2. Develop and maintain dashboards and visualisations using tools such as Tableau, Power BI, or Looker. 3. Perform exploratory data analysis to uncover trends, patterns, and anomalies. 4. Build statistical models and predictive algorithms to support business initiatives. 5. Generate regular and ad‑hoc reports for stakeholders across functions. 6. Collaborate with data engineers to design efficient data pipelines and storage solutions. 7. Conduct A/B testing and experiment analysis to evaluate product changes. 8. Document analytical methodologies, findings, and recommendations clearly. 9. Stay updated with emerging analytics techniques and propose innovative solutions. 10. Ensure data governance, security, and compliance standards are adhered to. Tech Stack: SQL, Python (pandas, numpy, scikit‑learn), R, Tableau/Power BI, Excel, Git, AWS Redshift or Snowflake, JIRA. Growth Path: Starting as a Data Analyst, high performers can progress to Senior Analyst, Data Scientist, Analytics Manager, and eventually to leadership roles such as Head of Analytics or Chief Data Officer, depending on performance and skill development. Why Join Barclays? You will gain exposure to a global banking ecosystem, work on real‑world financial data, and receive mentorship from seasoned professionals. The bank invests heavily in employee development through structured training programs, certifications, and a vibrant internal community. Moreover, Barclays offers competitive compensation, flexible work arrangements, and a supportive culture that values diversity and innovation.

Barclays 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 🎯
Barclays Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Barclays 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, R, Data Visualization, Statistics, Excel, Problem Solving, Communication, Business Acumen) & 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
Barclays 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 Barclays as a Data Analyst?
Preparation Tip: Highlight Barclays'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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