Store Incentive Processing System

Apr 2023 - May 2023

Role: Back-end Developer

Project Link Access to this project is restricted because it runs in an internal environment.
Store Incentive Processing System thumbnail
Tech Stack

Overview

This project focused on building a backend processing system used to determine store incentive eligibility based on recurring operational performance data. The application runs periodically, evaluates records using business rules, and helps operational teams identify which stores qualify for incentives in a more consistent and automated way.

In Collaboration With: Internal Development Team

Responsibilities

  • Requirement Analysis
  • Backend Processing Development
  • Database Logic Implementation
  • Data Processing and Transformation
  • Periodic Job Handling
  • Testing and Validation

Outcome

The project helped simplify incentive calculation by processing large volumes of operational data automatically and classifying the results into eligible and non-eligible groups. It reduced manual work, improved consistency, and created a more reliable foundation for reporting and follow-up operational processes.

Detailed Breakdown

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The business process needed a more dependable way to decide which stores qualified for incentives based on repeated operational evaluations. A manual approach would take more time and increase the risk of inconsistency, so this project introduced a backend processing flow that could evaluate data automatically and generate structured results for the business team.

My main contribution was on the core backend and database-side processing logic. I focused on how the data was prepared, processed, and classified during each execution cycle so the system could produce accurate and repeatable outcomes.

Primary Flow

01

Operational performance data is collected and prepared as the main input for the incentive evaluation cycle.

02

The system applies predefined business rules to determine whether each record meets the incentive criteria.

03

The results are classified into eligible and non-eligible groups, then prepared for operational review and reporting.

This project centered around a periodic backend processing module that evaluates operational data and determines incentive eligibility for stores. The system was designed to support a repeatable evaluation cycle and help the business team review results more efficiently.

Implementation Flow

01

Backend processing logic handles validation, transformation, and structured execution of the evaluation flow.

02

The system processes recurring data in a consistent way so the same rules can be applied reliably across each period.

03

The output is stored in a structured format that supports downstream business usage such as review, reporting, and follow-up processes.

Implementation Details

  • Backend data processing system
  • Python-based processing flow
  • PostgreSQL-based data handling
  • Rule-based evaluation pipeline
  • Recurring execution flow for periodic evaluation
  • Supported deployment to Google Cloud with assistance from the research team
  • Structured output for reporting and operations
  • Testing and validation to maintain processing accuracy

Some system names, data structures, and implementation details have been intentionally generalized because this was an internal enterprise project.

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