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Applications open Full-Time Job

Data Analyst with SQL/Python/Data visualization

Citigroup

  • India (Remote / Multiple), India
  • 6-8 LPA
  • 3-5 Years
  • Posted Oct 28, 2026
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About the role

Citi is a global financial services powerhouse with a presence in more than 100 countries. In India, Citi operates across banking, capital markets, and wealth management, offering a dynamic environment where technology and finance intersect. The company invests heavily in digital transformation, data‑driven decision making, and innovative solutions for its clients. As a fresher‑friendly organization, Citi provides structured onboarding, mentorship programs, and clear career ladders for early‑career professionals. The Data Analyst role at Citi’s Haryana office is designed for fresh graduates who are eager to apply their analytical skills to real‑world financial data. You will work closely with senior analysts and business stakeholders to extract insights, build dashboards, and support data‑centric initiatives across the bank. The position offers exposure to large‑scale data pipelines, modern visualization tools, and a collaborative culture that values curiosity and continuous learning. Key Responsibilities: 1. Extract, clean, and transform data from relational databases using SQL. 2. Develop Python scripts for data manipulation, statistical analysis, and automation of routine tasks. 3. Create interactive visualizations and dashboards using tools such as Tableau or Powerβ€―BI to communicate insights to business users. 4. Perform exploratory data analysis to identify trends, anomalies, and opportunities for process improvement. 5. Assist in maintaining data quality standards and documentation of data lineage. 6. Support the preparation of regular and ad‑hoc reports for senior management. 7. Collaborate with cross‑functional teams to understand data requirements and translate them into technical solutions. 8. Participate in code reviews and knowledge‑sharing sessions to foster best practices. 9. Contribute to the design of data models and assist in database schema enhancements. 10. Stay updated with emerging data‑analytics technologies and suggest innovative approaches. Tech Stack: SQL, Python (pandas, numpy, matplotlib), Tableau/Powerβ€―BI, Excel, Git, basic Linux commands. Growth Path: Starting as an Analyst, high performers can progress to Senior Analyst, then to Data Scientist or Analytics Manager within 2‑4 years, with opportunities to move across business lines such as risk, finance, or digital banking. Why Join Citi: You will be part of a globally recognized brand that values data as a strategic asset. Citi offers a structured learning environment, exposure to financial data at scale, and a clear roadmap for career advancement. The company’s inclusive culture, flexible work arrangements, and emphasis on work‑life balance make it an attractive destination for fresh talent looking to launch a rewarding analytics career.

Eligibility & process

Who can apply

Graduates with a B.Tech/B.E/MCA/BS in Computer Science, Information Technology, Electronics, or related fields. Minimum 60% aggregate (or CGPA 6.0/10). Batch year 2025‑2027. No active backlogs at the time of joining. Strong academic record in quantitative subjects is preferred.

Skills & stack

SQL Python Data Visualization Tableau Power BI Advanced Excel Statistics Git

Selection process

  1. Round 1: Online Aptitude & Logical Reasoning
  2. Round 2: Technical Interview (SQL/Python/Data Visualization)
  3. Round 3: HR Interview

Prep kit

20 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
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, Tableau, Power BI, Advanced Excel, Statistics, Git) & 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 Citigroup Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 5
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.
Behavioural & HR questions 3
Why do you want to join Citigroup as a Data Analyst with SQL/Python/Data visualization?
Highlight Citigroup'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.
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?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Citigroup 6-8 LPA
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