Back to selected work
E-COMMERCE · MOBILE ENGINEERING

OthAim Store.

Maintainable shopping experiences for Android and iOS, with product analytics built into the journey.

ROLESoftware Developer · Flutter
COMPANYTru India
PERIODNov 2025 — Present

Conceptual illustration of the product workflow, created for this case study.

01 / RESPONSIBILITY

What I owned.

Develop e-commerce features within a product team, contributing reusable widgets, analytics instrumentation, code reviews, and cross-functional delivery.

02 / CONTEXT

The problem behind the product.

A cross-platform commerce product needs consistent behavior across screens and devices, while product teams need visibility into how customers use the application.

03 / SYSTEM DESIGN

Connecting the pieces.

Build Android and iOS features with Flutter, Clean Architecture, and BLoC. Use reusable widgets for consistency and Firebase Analytics with MoEngage to instrument user journeys.

  1. 01Customer journey
  2. 02Flutter UI
  3. 03BLoC state
  4. 04Feature services
  5. 05Product analytics
Simplified logical flow; individual integrations have their own lifecycle.
04 / TRADE-OFFS & IMPLEMENTATION

The decisions that matter.

01

Give features clear boundaries

Clean Architecture and BLoC separate presentation, state, and application responsibilities to keep feature work maintainable.

02

Make reuse a product advantage

Shared widgets help screens behave consistently and reduce repeated implementation as commerce features evolve.

03

Connect delivery with measurement

Firebase Analytics and MoEngage instrumentation support product and growth analysis alongside sprint planning and code review.

05 / DELIVERY

From architecture to working software.

  • Contribute Android and iOS e-commerce features.
  • Build reusable components for consistent product behavior.
  • Instrument journeys to support product and growth analysis.

Thinking about scale & reliability

As the feature set grows, I focus on clear state boundaries, predictable shared components, and consistent analytics events. These make it easier for a product team to understand behavior, diagnose issues, and extend the application.

Want to talk through the architecture?

Let’s get into the details
NEXT CASE STUDY

Profertility