Manager - Analytics

IndiGo (InterGlobe Aviation Ltd); Gurugram District; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

IndiGo (InterGlobe Aviation Ltd) is seeking a Manager – Analytics within the Data Analytics & Operations Research team in Flight Operations. The role leads Analytics, OR and ML, delivering dashboards and analytical products for crew planning, pilot performance, fatigue risk management, fuel efficiency and sickness monitoring.

It includes people management and stakeholder coordination across Flight Ops. The position is a replacement role with responsibility for continuity of leadership reporting

Qualifications

• 6–9 years of experience in data analytics, BI or OR with 2–3 years of team leadership.
• Proven track record of production dashboards and automated reporting in fast-paced ops.
• Prior aviation/flight ops or crew rostering experience is preferred.

Responsibilities

• Lead Analytics, OR and ML branch; own dashboards, data structuring and automation.
• Maintain leadership dashboards covering pilot performance, crew metrics and compliance.
• Automate manual reporting and standardize data refresh ownership.
• Collaborate with Crew Planning, Line Operations and Leadership to deliver insights.
• Ensure data accuracy, validation and audit-readiness per regulatory requirements.
• Mentor and guide junior analysts; uphold quality/visualisation standards.
• Support ML use cases like absenteeism, fatigue and attrition; integrate with Fabric/Lakehouse.

Skills

SQL

Python

Power BI

Data Modelling

Stakeholder Mgmt

Leadership

Education

Bachelor’s/Master’s in Engineering/CS/Data Science/Maths

Tools

Microsoft Fabric

Snowflake

Delta Tables

Power Automate

Job description

Brief Introduction About The Role

The Manager – Analytics is a core leadership role within the Data Analytics & Operations Research team in Flight Operations. The role leads the Analytics, Operations Research and Machine Learning branch, and is responsible for the end-to-end design, development, automation and governance of business-critical dashboards and analytical products that support crew planning, pilot performance measurement, fatigue risk management, fuel efficiency, sickness/absence monitoring and leadership utilisation. Beyond technical delivery, the role carries people-management responsibility – guiding and mentoring analysts, managing stakeholder expectations across Flight Ops verticals, and ensuring timely, accurate and decision-ready data solutions. This is a replacement position for the incumbent Manager who is exiting the organisation, and is critical to maintaining continuity of recurring leadership reporting and ongoing analytics programmes.

Brief Introduction About The Role

The Manager – Analytics is a core leadership role within the Data Analytics & Operations Research team in Flight Operations. The role leads the Analytics, Operations Research and Machine Learning branch, and is responsible for the end-to-end design, development, automation and governance of business-critical dashboards and analytical products that support crew planning, pilot performance measurement, fatigue risk management, fuel efficiency, sickness/absence monitoring and leadership utilisation. Beyond technical delivery, the role carries people-management responsibility – guiding and mentoring analysts, managing stakeholder expectations across Flight Ops verticals, and ensuring timely, accurate and decision-ready data solutions. This is a replacement position for the incumbent Manager who is exiting the organisation, and is critical to maintaining continuity of recurring leadership reporting and ongoing analytics programmes.

Role / Designation:

Manager – Analytics (Data Analytics & Operations Research)

Location:

Gurgaon

Qualifications & Experience

• Bachelor’s or Master’s degree in Engineering, Computer Science, Data Science, Statistics, Mathematics, Operations Research or a related quantitative discipline; an MBA / analytics specialisation is an added advantage.
• 6–9 years of experience in data analytics, business intelligence or operations research, including at least 2–3 years of team-leading / people-management experience.
• Proven track record of independently designing, building and owning production-grade dashboards and automated reporting solutions in a fast-paced operational environment.
• Prior experience in aviation / airline Flight Operations, crew rostering or a similarly regulated, data-intensive domain is strongly preferred.

Skills & Knowledge

• Advanced SQL and Python for data extraction, transformation, automation and analysis.
• Strong hands-on expertise in Power BI / DAX, data modelling and visualization best practices.
• Working knowledge of Microsoft Fabric, Lakehouse / Delta tables, Snowflake and Power Automate workflow automation.
• Ability to translate operational and regulatory requirements (FDTL, fatigue, compliance, leave/sickness rules) into robust analytical logic.
• Strong stakeholder management, communication and requirement-gathering skills across leadership and cross-functional teams.
• Demonstrated people-leadership ability – mentoring analysts, setting quality/visualisation standards and running feedback loops.

Job Responsibility

• Lead the Analytics, Operations Research and Machine Learning branch – owning dashboard development, data structuring, visualization and automation.
• Own and maintain the suite of recurring leadership dashboards and reports covering pilot performance, fuel efficiency, leadership utilization, crew sickness/absence, compliance and operational monitoring.
• Drive automation of manual reporting processes and standardize refresh ownership to reduce recurring manual effort.
• Partner with Crew Planning, Roster Escalation, Line Operations, Training and leadership stakeholders to translate business needs into analytical deliverables.
• Ensure data accuracy, validation and audit-readiness across all reporting, in line with regulatory and DGCA requirements.
• Guide and mentor junior analysts on technical tasks, data structuring and visualization standards; ensure timely, high-quality delivery.
• Support advanced initiatives – machine-learning use cases (absenteeism, fatigue, attrition, standby prediction) and integration with the wider Fabric / Lakehouse analytics stack.
• Provide decision-ready insights and ad-hoc analysis to leadership to support crew welfare, cost optimisation and operational efficiency.