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Lead Data Analyst (Pricing Strategy) at Confidential (Sports/Entertainment Hub)

This role is a high-level strategic position focused on the intersection of Sports/Entertainment and Advanced Data Science. Based on the specific tech stack (Databricks Lakehouse, dbt, SQL) and the focus on variable ticket pricing, this position is likely with a major sports franchise, a stadium management group, or an elite ticketing platform operating out of Bengaluru.

🟢 Role Overview & Impact

You will lead the data strategy for a Business Intelligence & Analytics department, specialising in Dynamic Ticket Pricing. This is a 360-degree role where you own the lifecycle from raw data ingestion to real-time pricing adjustments during a live season.

  • Revenue Architect: You aren’t just reporting numbers; you are creating game-specific models to adjust inventory and pricing in real-time to maximise revenue.

  • Modern Data Stack: You will be responsible for building dbt pipelines to transform raw data (concessions, ticketing, social engagement) into clean, analytical models.

  • Real-Time Visualisation: Using Databricks SQL, you will build live executive dashboards that track fan behaviour and stadium operations as they happen.

  • Fan Personalisation: You will perform advanced database segmentation to ensure marketing communications reach the right fans at the right time.

📊 Compensation & Salary Benchmarks (2026)

Based on verified 2026 salary data for Lead/Senior Analytics roles in Bengaluru:

Metric Details
Average CTC (6+ Years) ₹22.6 LPA – ₹32 LPA
Top 10% Percentile ₹35.7 LPA – ₹50.2 LPA+ (Common for candidates with dbt/Databricks mastery).
Market Context Demand for “Pricing Analytics” is currently peaking in the entertainment and retail sectors, often leading to performance-based bonuses.

🎯 Required Tech Stack & Qualifications

  • Education: Degree in a quantitative field (CS, Stats, Math, or Economics).

  • Experience: 6+ Years in an analytical role (with 5+ years in SQL & Python).

  • dbt Mastery: At least 3+ years of experience architecting pipelines with dbt.

  • Pricing Expertise: Proven experience in dynamic or variable pricing models is highly preferred.

  • Problem Solving: A critical thinking mindset capable of delivering “unique and actionable” solutions.

     

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