Manager - Business Analytics & Data Engineering - FMCG/Retail

- This role is with a fast growing company deals in NUTRITIONAL PRODUCTS & FOOD SUPPLEMENTS & selling their products through Retail & Modern Trade
- We are looking for a candidate coming from a start-up and Retail / Modern Trade background with a strong knowledge of how a retail business operates.
Work location - Hyderabad (5 days a week)
Purpose of the JOB:
Analytics Lead role exists to drive data-driven decision-making across the company. The role will be responsible for building scalable data pipelines, managing data lakes, developing automated analytics workflows, and delivering impactful dashboards and visualizations using tools such as Power BI, Azure and MS Excel.
The ideal candidate will come from combine strong data engineering capabilities (ETL, data lakes, query automation) with analytics and visualization expertise to enable business teams to access reliable, real-time insights.
Key job responsibility:
Data Engineering & Infrastructure:
- Design, develop, and maintain ETL pipelines to ingest, transform, and load data from multiple sources.
- Build and manage enterprise data lakes and data warehouses on Azure.
- Ensure data quality, integrity, and governance across the data ecosystem.

- Optimize data storage and query performance for analytics use cases.
Market & Competitor Intelligence:
- Conduct competitor analysis including product positioning, pricing strategies, market share, and performance trends.
- Track and analyse competitor activity across digital channels, marketing campaigns, and product launches.
- Build competitive benchmarking dashboards to inform strategy and leadership decisions.
Social Media & Digital Intelligence:
- Design and implement social media scraping and monitoring frameworks across platforms (e.g., Tik Tok, LinkedIn, Instagram, forums etc).
- Analyse sentiment, trends, and consumer conversations related to the company and competitors.
- Identify emerging market trends, influencers, and customer feedback signals.
Customer Profitability & Business Analytics:
- Conduct customer profitability and cohort analysis to identify high-value customer segments.
- Build models for customer lifetime value (CLV), acquisition cost (CAC), and retention analysis.
- Support marketing, product, and sales teams with data-driven insights on customer behaviour and revenue drivers.
Data Visualization & Analytics:
- Develop interactive dashboards and reports using Power BI and other BI tools.
- Translate complex datasets into clear, actionable visual insights for stakeholders.
- Create standardized reporting frameworks and reusable dashboards for business teams.
Automation & Data Querying:
- Build automated queries and workflows to streamline data extraction and reporting.
- Implement automated data refresh pipelines and scheduling.
- Develop reusable SQL scripts and analytical models to support decision making
Budget: 30LPA to 35LPA