L #2981
Applications open
Full-Time Job
Python Developer
Infosys
About the role
- Strong experience in Python development
- Good understanding of SQL and data handling
- Experience working in production environments Strong proficiency in Python (data manipulation, scripting, automation) Advanced knowledge of SQL (joins, subqueries, window functions, performance tuning) Hands-on experience with ETL/ELT tools or frameworks Experience working with relational databases (e.g., MySQL, PostgreSQL, SQL Server, Oracle) Solid understanding of data warehousing concepts (fact/dimension tables, star schema) Ability to work with large datasets and optimize data processing workflows Strong analytical, problem-solving, and debugging skills
- Design, develop, and maintain Python applications
- Write clean, efficient, and reusable Python code
- Develop data processing and automation scripts
- Work with databases using SQL
- Perform code reviews and guide junior developers
- Troubleshoot application and data issues
- Support production deployments and enhancements Develop, maintain, and optimize ETL pipelines to ingest, transform, and load data from multiple sources Write efficient, scalable, and well-documented Python scripts for data processing and automation Design and optimize complex SQL queries, views, and stored procedures for performance and accuracy Perform data validation, quality checks, and reconciliation to ensure data integrity Troubleshoot and resolve data pipeline failures and performance issues Collaborate with data analysts, data scientists, and business teams to understand data requirements Implement best practices for data security, governance, and compliance Maintain technical documentation for ETL workflows and data models
Experience with cloud platforms (AWS, Azure, or GCP) Familiarity with big data technologies (Spark, Hadoop) Exposure to workflow schedulers (Airflow, Prefect, Cron) Knowledge of CI/CD pipelines and version control (Git) Understanding of data governance and lineage tools
Eligibility & process
Who can apply
Employment type: Full-time
Skills & stack
Selection process
Details are shared by the recruiter after shortlisting.
Prep kit
20 resourcesStudy material 4
Aptitude Practice Questions & Mock Tests
Curated logical, quantitative, and verbal reasoning problems for the initial online screening round.
Company-Specific Interview Preparation Corner
Detailed interview experiences, exam formats, and previous test questions for Infosys and tech roles.
Technical Placement Question Bank
High-yield coding cheat sheets, core CS fundamentals (OOP, DBMS, OS, Networks), and rapid revision guides.
Algorithm, DSA & Live Code Debugger Practice
Hands-on problem sets to improve coding speed and step-by-step memory debugging.
Company-specific guides 4
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.
COMPANY GUIDE
Infosys Interview Preparation Corner
Comprehensive guide covering typical interview formats, common questions, and preparation tips for Infosys and off-campus tech roles.
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.
CODING PRACTICE
Algorithm and Data Structure Problem Set
Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.
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 (Python, SQL, PostgreSQL, MySQL, Oracle DB, SQL Server, AWS, Azure) & 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
Infosys 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 Infosys as a Python Developer?
Highlight Infosys's market reputation, recent tech innovations, and how your skills in Python directly solve their team's objectives.
Highlight Infosys'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.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
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.
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Competitive Package
Bengaluru, India
Employment type: Full-time
