Senior Data Analyst

airtel; Gurugram District; On-site; INR 3,800,000 - 7,000,000; Full time

Job summary

Airtel is seeking a DGM - Analytics to lead the analytics function end to end, partnering with business heads and leadership to shape strategy and dive deep into data. You will mentor a team of analysts and establish KPI dashboards to drive data-driven decisions that scale the business.

The role requires strong SQL and Python, plus expertise in BI tools, data warehouses and cloud platforms, with 6-8 years of analytics leadership experience.

Qualifications

• Bachelor's degree in Engineering, Statistics, Mathematics, Economics or related field; MBA or quantitative masters preferred.
• 6-8 years in analytics, BI or data science with prior team leadership experience.
• Proven ability to influence senior leadership with data-driven insights.

Responsibilities

• Lead, mentor and grow a team of analysts; set goals, review quality and build talent.
• Act as analytics partner to business heads and leadership; translate questions into analyses.
• Define operating rhythm, prioritization, intake, review standards and documentation.
• Own analytics roadmap, KPI frameworks, dashboards and data governance.
• Develop problem framing, data querying, modelling and storytelling for decisions.

Skills

SQL

Python

Data visualization

Statistics

Forecasting

Experimentation

Education

Bachelor's degree

MBA preferred

Tools

Power BI

Tableau

Looker

Data warehouses

Job description

The DGM - Analytics leads the analytics function end to end: a team of analysts, the partnership with business and leadership, and the search for where the business can grow next. This is a senior, high-visibility role for someone who can shape strategy at the leadership table and still go deep on the data when needed.

Key Responsibilities

Team leadership

• Lead, mentor and grow a team of analysts; set clear goals, review work quality and build a strong talent pipeline.
• Define the team's operating rhythm: prioritization, project intake, review standards and documentation.
• Develop analysts' technical depth and business thinking through coaching, feedback and stretch assignments.

Stakeholder management and leadership partnership

• Act as the primary analytics partner to business heads and senior leadership, translating business questions into analytical problems.
• Present insights, recommendations and trade-offs to leadership in clear, decision-ready form.
• Manage expectations, timelines and competing priorities across multiple stakeholders.

Gap identification and business scaling

• Proactively diagnose gaps in performance, processes, funnels, customer experience and data availability.
• Identify and size opportunities to scale the business, such as new segments, channels, products, pricing levers and efficiency gains.
• Turn findings into prioritized action plans with owners, metrics and expected impact, and track them to closure.

Analytics strategy and governance

• Own the analytics roadmap and align it with business goals.
• Establish KPI frameworks, dashboards and single sources of truth for decision-making.
• Drive data quality, governance and adoption of self-serve analytics across the organization.
• Work independently on complex analyses, from framing the problem and querying data to modelling and storytelling, without waiting for direction.
• Guide the use of advanced techniques (statistical modelling, forecasting, segmentation, experimentation, ML where it adds value).
• Evaluate and introduce tools, automation and best practices that raise the team's productivity.

Qualifications and Experience

• Bachelor's degree in Engineering, Statistics, Mathematics, Economics or a related field; an MBA or master's in a quantitative discipline is preferred.
• 6-8 years of experience in analytics, business intelligence or data science, with a prior experience of leading teams of analysts.
• Proven track record of partnering with senior leadership and influencing business decisions with data.
• Demonstrated impact: examples of growth, revenue, cost or efficiency gains driven by analytics.
• Experience in fintech is an advantage.

Skills and Competencies

Technical

• Strong command of SQL and at least one analytics language (Python or R); able to build and review hands-on analyses.
• Expertise in BI and visualization tools (Power BI, Tableau, Looker or similar).
• Solid grounding in statistics, forecasting, experimentation and predictive modelling.
• Familiarity with data warehouses, cloud platforms and modern data stacks.