Results that
speak for themselves

A clinical research platform managing trial scheduling, procedures, and financials needed embedded analytics as part of their product offering. Their customers demanded self-service reporting but the engineering team lacked BI expertise.

Designed and integrated an enterprise-grade BI layer directly into the SaaS product using Looker Enterprise connected to BigQuery. Built a semantic data model covering trial workflows, patient scheduling, and financial metrics — enabling end-users to explore data without SQL knowledge.

• Embedded analytics shipped as a premium product feature
• Self-service reporting for 100+ clinical research teams
• Reduced ad-hoc data requests to the engineering team by 70%

A student lending company had marketing data scattered across multiple ad platforms and internal systems. No unified view of campaign performance, CAC, or channel attribution — making budget decisions guesswork.

Built end-to-end marketing BI from scratch: data ingestion pipelines from all advertising platforms and internal systems, a transformation layer with business logic, a centralized data warehouse, and executive dashboards with real-time marketing KPIs.

• Single source of truth for all marketing data
• Real-time CAC and ROAS visibility across all channels
• Data-driven budget reallocation that improved overall marketing efficiency

A digital marketing agency managing paid campaigns across Meta, Google, and TikTok for 10-15 e-commerce clients needed server-side tracking integrations and cross-client reporting — but had no data engineering capacity.

Integrated each client's e-commerce platform with advertising APIs for server-side conversion tracking, enabling the ad platforms' optimization algorithms to work with first-party data. Built a unified reporting layer across all clients and channels.

• 10-15 e-commerce stores integrated with ad platforms
• Server-side tracking improved ad optimization accuracy
• Centralized cross-client reporting saved 20+ hours/week of manual work

A fast-growing fresh grocery delivery startup in NYC had outgrown their legacy data warehouse. Queries were slow, costs were rising, and the analytics team couldn't keep up with the business's need for real-time operational insights.

Migrated the entire data warehouse to Snowflake with a redesigned schema optimized for their delivery operations. Rebuilt transformation pipelines and ensured zero-downtime transition with parallel running of old and new systems.

• Query performance improved by 5x after migration
• Infrastructure costs reduced through Snowflake's usage-based pricing
• Analytics team unblocked with self-service access to operational data

A marketing agency specializing in brand promotion was manually pulling data from multiple advertising platforms into spreadsheets. Reporting took days, was error-prone, and couldn't scale with their growing client base.

Automated data collection from all major ad platforms (Google Ads, Meta, TikTok, LinkedIn) into a centralized warehouse. Built automated reporting pipelines with scheduled dashboard refreshes and anomaly alerting.

• Reporting time reduced from days to minutes
• Automated anomaly detection caught budget overspends early
• Scalable infrastructure ready for 3x client growth

A subscription-based e-commerce company had no analytics infrastructure. Business decisions were made on gut feeling. They needed full visibility into customer lifecycle, churn, LTV, and marketing attribution — fast.

Delivered end-to-end analytics: from raw data ingestion (Shopify, Stripe, ad platforms) through a modular dbt transformation layer to interactive dashboards. Built subscription-specific models including cohort analysis, MRR tracking, churn prediction, and LTV calculations.

• Complete visibility into subscription metrics (MRR, churn, LTV)
• Cohort analysis revealed key churn drivers, enabling targeted retention
• Marketing attribution model connected ad spend to actual subscriber value