Unlocking marketing insights from GA4 at scale

Provide a robust, cost-aware GA4 data model with business logic so teams can analyze traffic, conversion, and revenue drivers without engineering bottlenecks.

• Incremental GA4 model: Built scalable pipelines with sessionization, attribution, and channel logic tuned for big volumes.
• Cost and performance stewardship: Partitioning, clustering, and pruning to control compute while keeping SLAs.
• Analyst-ready layer: Standardized dimensions and metrics for downstream analysis and experimentation.
• Validation and scenarios: Reconciled to financials, added what-if views for pricing, mix, and cost changes.

Rollout framework:

1. Strategy and alignment workshops with business and tech
2. Technical discovery with domain teams
3. Foundation rollout for infra, security, CI/CD, and branching
4. Enablement and onboarding for users and developers
5. Continuous improvement for migration, maintenance, and support

Migration at scale: An agentic migration assistant to port MS SQL objects into dbt, first 1:1, then automated refactoring, delivering an estimated 80% speed-up versus prior manual approaches.

• Faster analysis for growth/marketing teams, leading to better conversion and traffic insights.
• Lower maintenance burden through engineered, incremental pipelines.
• A reusable foundation for experimentation and forecasting.
• Future-ready: A strong base for analytics, ML, and automation across multiple domains.