Data Analyst

airtel; Gurugram District; On-site; INR 1,200,000 - 2,200,000; Full time

Job summary

Airtel is seeking an analytics-driven professional to collaborate with Business, Product, Technology and Operations to translate complex requirements into actionable data insights.

The role focuses on building scalable data solutions, dashboards, and AI-enabled analytics to influence strategic decisions across the organization.

Qualifications

• Hands-on technically with SQL, Python, Tableau and large datasets.
• Independently identify data sources, define analytical logic, and build robust solutions.
• Develop advanced analytical models, automation frameworks, and reusable datasets.
• Build intuitive dashboards and data storytelling to drive decisions.
• AI-native mindset with experience in AI-enabled solutions.

Responsibilities

• Partner with cross-functional teams to identify and define high-impact business problems.
• Translate ambiguous requirements into structured analytical statements and hypotheses.
• Independently identify data sources and build robust analytical solutions.
• Generate actionable insights that influence business strategy and decisions.
• Build dashboards using Tableau or similar tools and tell data-driven stories.
• Identify opportunities to leverage AI to improve workflows and decision making.

Skills

SQL

Python

Tableau

Large datasets

Job description

• Partner closely with cross-functional teams across Business, Product, Technology, Operations, Risk, and other functions to identify and define high-impact business problems.
• Translate ambiguous business requirements into structured analytical problem statements and actionable hypotheses.
• Independently identify relevant data sources, define analytical logic, and build robust solutions.
• Generate actionable insights that influence business strategy and decision-making.

2. Data & Technical Expertise

• Work extensively with large and complex datasets to extract, process, and analyse information.
• Build efficient and scalable data solutions using SQL and Python.
• Develop advanced analytical models, automation frameworks, and reusable datasets.
• Ensure accuracy, robustness, and scalability of analytical solutions.

3. Dashboarding & Data Storytelling

• Build intuitive and insightful dashboards using Tableau or similar visualization tools.
• Go beyond reporting by identifying the underlying business drivers and translating data into actionable insights.
• Develop self-service analytical solutions that enable stakeholders to independently access relevant information.

4. AI & Advanced Analytics

• Identify opportunities to leverage AI and Generative AI to improve analytical workflows, business decision-making, and operational efficiency.
• Build and experiment with AI-enabled solutions, including applications leveraging LLMs, automation, and intelligent decision systems.
• Drive the adoption of AI within analytics to reduce manual effort and improve the speed and quality of insights.
• Stay updated with emerging AI technologies and translate relevant capabilities into practical business use cases.

5. Cross-functional Collaboration

• Work directly with senior stakeholders to understand business challenges and independently drive analytical initiatives.
• Collaborate with Data Engineering, Technology, Product, and Business teams to ensure the availability and usability of relevant data.
• Act as a bridge between business and technical teams by converting business problems into clear analytical requirements.

6. Ownership & Execution

• Take complete ownership of analytical initiatives from problem definition to implementation and impact measurement.
• Proactively identify opportunities and problems rather than waiting for detailed instructions.
• Operate effectively in an ambiguous and fast-paced environment.
• Challenge existing approaches and continuously look for opportunities to improve processes, tools, and decision-making.

What We Are Looking For

The ideal candidate is:

• High on ownership, taking responsibility for outcomes rather than just completing assigned tasks.
• Hands-on technically, with the ability to independently work with SQL, Python, Tableau, and large datasets.
• AI-native, with practical experience experimenting with and building AI-enabled solutions.
• Business-oriented, with the ability to engage confidently with senior stakeholders and influence decisions.
• Collaborative, with a strong ability to work across functions and bring different teams together to solve problems.