Data Analyst

Indigo’s interview process typically starts with a timed online aptitude test covering quantitative, logical and data interpretation questions. Successful candidates move to a technical interview focusing on SQL queries, Python coding, statistical concepts and case‑study discussions. The final HR round assesses cultural fit, communication skills and motivation. Overall difficulty is moderate, and thorough preparation of analytics fundamentals and problem‑solving techniques greatly improves chances.

Indigo promotes a collaborative and performance‑oriented culture where employees are encouraged to experiment with data to drive business outcomes. The airline offers structured growth paths, regular upskilling sessions and a healthy work‑life balance, with flexible timings for analytical roles.

Graduates (B.Tech/B.E., B.Sc., M.Sc.) in Computer Science, Information Technology, Statistics, Mathematics, Engineering or related fields; Minimum 60% aggregate (or CGPA 6.0/10); Freshers from batch 2025‑2027; No active backlogs at the time of joining; Must be eligible to work in India.

Round 1: Online Aptitude Test → Round 2: Technical Interview (Data Analytics) → Round 3: HR Interview

Indigo, officially known as InterGlobe Aviation Ltd., is India’s largest low‑cost carrier and has consistently been recognized for its operational efficiency, on‑time performance and customer‑centric approach. With a fleet of over 250 aircraft serving more than 80 domestic and international destinations, the airline has built a data‑driven culture to optimise everything from route planning to passenger experience. The company’s rapid growth creates a fertile ground for fresh talent to contribute to strategic decisions that shape the future of Indian aviation. The Data Analyst role at Indigo is designed for fresh graduates who are passionate about turning raw data into actionable insights. As a member of the analytics team, you will work closely with product managers, business stakeholders and data engineers to understand complex business problems and deliver data‑centric solutions that drive revenue, improve operational efficiency and enhance customer satisfaction. This position offers a unique blend of analytical rigor and business exposure, making it an ideal launchpad for a career in data science and analytics. Key Responsibilities: 1. Collaborate with business units to define problem statements and translate them into analytical projects. 2. Extract, clean, and transform large datasets from multiple sources using SQL and Python. 3. Perform exploratory data analysis to uncover trends, patterns and anomalies. 4. Build and validate predictive models (regression, classification, clustering) to support decision‑making. 5. Develop interactive dashboards and visualisations using Tableau/PowerBI for stakeholder consumption. 6. Deploy models into production environments and monitor their performance over time. 7. Document methodology, code and findings to ensure reproducibility and knowledge sharing. 8. Communicate insights and recommendations clearly through presentations and reports. 9. Participate in cross‑functional meetings to align analytics initiatives with business goals. 10. Stay updated with emerging tools and techniques in data science and suggest improvements to existing workflows. Tech Stack: Python (pandas, scikit‑learn), R, SQL, Tableau, PowerBI, Git, AWS (S3, EC2, SageMaker), Excel. Growth Path: Junior Data Analyst → Data Analyst → Senior Data Analyst → Data Scientist → Analytics Manager → Head of Analytics. Indigo encourages continuous learning through internal training programs, certifications and mentorship, enabling rapid career progression for high‑performers. Why Join Indigo? You will be part of a fast‑growing airline that values data‑driven decision making, offering exposure to real‑world problems that impact millions of passengers. The role provides a collaborative environment, competitive compensation, and a clear roadmap for professional development, making it an excellent starting point for aspiring data professionals.