Enzo LABAT

Dating app for iOS and Android. €1M+ ARR,~4M messages per month. • Led the migration of chat from vendor CometChat to an in-house Firestore backend: data model, conversation lifecycle, send pipeline, push notifications, unread counters, reactions. Switched 100% of traffic in two weeks with no loss of activity (683K → 880K messages/week), cutting a five-figure annual vendor cost. • Built the conversation backend in TypeScript on Cloud Functions: metadata, hard deletion and purge, createConversationV1 /leaveConversationV1 APIs, data migrations. Enabled App Check and hardened Firestore security rules. • Shipped identity verification with Yoti: replaced a "verified" boolean with a verification status state machine, rolled out behind feature flags (mandatory for men, optional for women). • Rearchitected the app across 60+ workstreams delivered as stacked merge requests: navigation moved to GoRouter StatefulShellRoute, home page god object split, nine onboarding screens rebuilt on a presenter architecture, critical lint rule re-enabled repo-wide. • Delivered Mystery Card, an ice-breaker feature: 56,000 sends in three weeks, used by one conversation opener in three. Also the onboarding redesign, Match screen, inbox sorting, photo and camera revamp, five new languages. • Contributed to lifting 7-day retention of new users from ~11% to 23% (day-1: 15.5% → 21.9%) during the onboarding redesign.

Contributed to the mobile app redesign of a property investment platform, in the team owning the dashboard and asset portfolio. Flutter, Riverpod, BLoC, Freezed, fl_chart.

Migrated an in-store app used by employees in nine countries from Android to Flutter, cutting technical debt. Designed reusable internal packages: authentication, barcode scanner, UI components. Scandit, ML Kit, Firebase, Phrase.

Built the front end of both products of a sports-streaming startup: mobile app and web advertising platform. Integrated video streaming through AWS IVS. React Native, React.

Developed the mobile app and backend of a parcel-holding and home-services product for consumers.

Analytics integration with Google stack : - Google Analytics for key data on the product - Google Data Studio for data visualisation - Google Optimize for A/B testing Developed a data collection pipeline in Python Created a Linkedin scraper LinkedIn to extract profiles for HR hiring.

Built a ticket-activity monitoring dashboard on the Elastic stack and a cross-platform mobile app in React Native.