IndiGo – Data Analyst
The IndiGo interview process generally includes an online assessment followed by technical and HR interview rounds. The technical interview may focus on: Python programming SQL queries Data Analysis concepts Statistics fundamentals Machine Learning basics Problem-solving skills The final HR round typically evaluates communication skills, cultural fit, career expectations, and interest in the role.
IndiGo offers a fast-paced and performance-driven work environment. Employees get opportunities to work with cross-functional teams and solve real-world business problems. The organization also focuses on: Learning and upskilling Performance-based growth Collaboration across teams Exposure to large-scale business data Career opportunities in analytics and technology
Candidates should meet the following requirements: Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Engineering, or a related field. Preferred graduating batch: 2026. Strong foundation in programming, statistics, and data analysis. Good understanding of Python and SQL. Knowledge of Machine Learning concepts is preferred. No active backlogs, subject to company eligibility requirements. Minimum academic percentage/CGPA requirements may apply as per the official job notification.
Round 1: Online Aptitude Test → Round 2: Technical Interview (coding & concepts) → Round 3: HR Interview
IndiGo, officially known as InterGlobe Aviation Limited, is one of India's leading airlines and operates across a large domestic and international network. The Data Analyst role provides an opportunity for fresh graduates to work with data, analytics, business intelligence, and modern technologies. Candidates may collaborate with business teams, engineers, and analytics professionals to solve real-world business problems. As a Data Analyst, you may work on transforming raw data into meaningful insights that support better business decisions. Key Responsibilities Understand business requirements and convert them into analytical solutions. Perform data cleaning and exploratory data analysis. Work with large datasets using Python and SQL. Build dashboards and visualizations for business insights. Support machine learning and data-driven initiatives. Automate repetitive data analysis workflows. Collaborate with data engineering and business teams. Ensure data quality, accuracy, and reliability. Document findings and communicate insights to stakeholders. Stay updated with emerging technologies such as AI, GenAI, and MLOps. Tech Stack Python SQL Machine Learning Statistics Data Visualization Databricks Snowflake Azure / AWS Deep Learning / GenAI Docker / Kubernetes MLflow and MLOps Tools Career Growth Candidates joining as Data Analysts can potentially grow into roles such as: Data Analyst ↓ Senior Data Analyst ↓ Data Scientist / Analytics Specialist ↓ Analytics Lead There may also be opportunities to move into domains such as Product Analytics, Revenue Management, Business Intelligence, and Operations Analytics.
🔔 Apply before 04 Oct 2026 — 17 days remaining