Senior Data Engineer (Bengaluru)

Senior Data Engineer (Bengaluru)

20 Oct
|
Quantiphi
|
Bengaluru

20 Oct

Quantiphi

Bengaluru

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.

If working in an workplace that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!

Role: Senior Data Engineer - RGM Data Analyst

Experience Level: 3 to 7 Years

Work location: Bangalore, Mumbai & Trivandrum

Notice Period: 0-15 days (Looking for immediate joiners/ Serving Notic

Role Overview:

We are seeking a data-driven, Revenue Growth Management function focused Data Analyst to optimize our Trade Promotion Optimization (TPO) product and enhance trade investment decision-making. In this role, you will bridge the gap between technical data pipelines and commercial execution, working directly with backend data pipelines, algorithmic model outputs, and front-end TPO interfaces.

Your primary mandate will be to proactively monitor and audit data inputs and system-generated recommendations, identifying anomalies, bias, data drift, data integrity issues and counter-intuitive promotional plans before recommendations reach client’s RGM and Customer Account teams. You will collaborate closely with internal technical teams , and client RGM leads, using advanced analytical skills to translate algorithmic outputs into compelling, actionable commercial stories that drive profitable revenue growth through the retailer sell-in journey.

Responsibilities:

- Pre-emptive Model Diagnostics: Routinely audit backend data pipelines and optimization engine outputs to identify ingestion errors, pricing mismatches, and data drift before recommendations are published to end-users
- Recommendation Sanity Checks: Stress-test TPO engine outputs (optimal frequency, discount depth, promotional mechanics)



against commercial reality—identifying flawed recommendations stemming from contaminated baseline volumes, incorrect trade rates, or skewed price elasticities.
- Root-Cause Analysis: Partner with data engineering, Data Science and Optimization teams to diagnose and isolate issues across Data & DS pipelines and frontend reports
- Map TPO recommendations against real-world retailer trade architectures, customer calendars, and execution constraints to ensure feasibility during the retailer sell-in journey.
- Run scenario modeling and pre-/post-event evaluations to evaluate promotional ROI, cannibalization, halo effects, and trade spend efficiency across key accounts.
- Ensure data integrity by validating whether actual realized promotional plans and key metrics match with what is flowing into data and model pipelines
- Collaborate with data engineering, data science, optimization and UI/UX teams to continuously refine data feeds, system logic, and model tuning.
- Drive adoption of the tool by creating RGM focused content based on findings and data-driven insights

Technical Skills:

- SQL, Python and Excel for data analysis.
- Familiarity and comfort with using cloud based data and application environment like Azure and Databricks

Domain and Functional Skills:

● CPG industry experience and familiarity with commercial analytics, Price, Pack & Promotion planning and measurement

● Data-driven story telling and RGM functional acumen

● Familiarity with RGM workflows and KPI frameworks

● Strong understanding of RGM levers: Pricing, Price-Pack Architecture (PPA), Mix Management, Trade Terms, and Promotion Strategy.

● Familiarity and experience with POS, Shipment and CPG P&L; data

● Self-Directed Problem Solver: Ability to operate effectively within ambiguous client environments and formulate solutions with minimal hand-holding.

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

📌 Senior Data Engineer (Bengaluru)
🏢 Quantiphi
📍 Bengaluru

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