Most leadership teams operate in a fog of conflicting numbers. Marketing reports record lead volume that sales claims never existed; Google Analytics counts visitors that never registered in the database; and Stripe displays revenue figures that clash with internal accounting spreadsheets. When every department presents their own numbers, executive meetings degenerate into debates over whose spreadsheet formula is less broken. I engineer cohesive data architectures that establish an indisputable single source of truth. By building automated ETL pipelines, normalizing data schemas, and isolating analytical workloads from your transactional database, your business metrics align perfectly. From top-of-funnel ad spend down to user feature adoption and cleared bank revenue, leadership gains the clarity required to allocate capital with absolute confidence.
Discuss your projectThe final scope is agreed around your project.
We catalog where your data currently lives: production databases, billing platforms (Stripe), CRM tools, and advertising accounts. We identify schema discrepancies, duplicate records, and conflicting definitions to establish universal metric standards.
Extract, transform, and load. We build resilient data ingestion pipelines that automatically pull records from external APIs and internal systems, cleanse anomalies, and deposit them into an organized analytical warehouse.
Never run heavy analytical queries against your live production database. We structure dedicated dimensional models (star schemas, materialized views) optimized for lightning-fast aggregation and time-series reporting.
No vanity metrics or 40-chart sensory overload. We design clean, responsive dashboards (using Metabase, Grafana, or bespoke interfaces) displaying real operational vitals: Customer Acquisition Cost (CAC), Lifetime Value (LTV), cohort retention, and net revenue.
Pinpoint exactly where users experience friction. We implement granular, event-driven product tracking (using PostHog or custom server-side event collectors) to map user onboarding funnels, feature activation rates, and churn drop-off points.
Connect top-of-funnel advertising clicks and organic search impressions directly to actual closed contracts and cash collected in the bank, exposing which marketing channels yield profitable customers and which waste budget.
Bypass ad-blockers and ensure strict GDPR compliance. We implement first-party server-side tracking and privacy-respecting measurement (Cloudflare Web Analytics, Plausible) without exposing customer data to invasive third-party tracking pixels.
Key numbers delivered directly to your leadership channel. Daily Slack or email summaries keep founders informed of yesterday's revenue and signups, while automated anomaly monitors trigger immediate alerts if signup conversion suddenly drops.
We catalog where your data currently lives: production databases, billing platforms (Stripe), CRM tools, and advertising accounts. We identify schema discrepancies, duplicate records, and conflicting definitions to establish universal metric standards.
Data engineering must deliver instant analytical queries without endangering the stability of your production application. Depending on data scale, I implement pipelines using PostgreSQL read-replicas, DuckDB for local vectorized speed, or ClickHouse for high-throughput event analytics. Data transformations are modeled using SQL with typed validation. On the product tracking side, I deploy self-hosted PostHog or lightweight server-side telemetry to capture user interactions with zero client-side latency. Everything is visualized through clean, open-source BI platforms like Metabase or custom React/Next.js dashboard components tailored specifically to your executive workflow.
You can see this rigorous measurement architecture across my work: in New Leasing, where multi-channel acquisition signals and Google Search performance were unified with catalog engagement; and in Acquanova Sicilia, where digital advertising acquisition was tied directly into the CRM pipeline to measure verified business revenue.
Never under proper architecture. Amateur setups run heavy aggregation queries directly on their production database, causing locks and slowdowns for live users. I isolate analytical workloads using read-replicas, columnar databases (ClickHouse/DuckDB), or pre-computed materialized views refreshed asynchronously in the background. Your live customers never experience a millisecond of delay.
By utilizing privacy-first, server-side measurement architectures. Rather than loading invasive third-party ad pixels that track visitors across the web, we use first-party event collection and server-to-server APIs. By anonymizing IP addresses and storing data within European jurisdiction, you maintain rock-solid compliance while capturing 100% of your traffic free from ad-blocker loss.
Yes. That is the definition of true full-funnel measurement. By capturing unique click identifiers (such as UTM parameters and gclid/fbclid tokens) at the moment of lead capture and attaching them to the customer record in your CRM, we trace that lead through every sales milestone until invoice payment. You see the exact return on investment (ROAS) for every marketing euro spent.
Almost certainly not. Enterprise data warehouses charge enormous monthly fees and are designed for Fortune 500 enterprises with petabytes of data. For 99% of businesses, modern tools like ClickHouse, DuckDB, or an optimized PostgreSQL read-replica handle tens of millions of rows with sub-second response times at a fraction of 1% of the cost.
Yes. Eliminating engineering as a data bottleneck is a primary goal. By deploying intuitive business intelligence tools like Metabase or self-serve dashboards, we provide your sales, marketing, and operations teams with clean visual query builders and curated filters. Anyone on your team can generate charts and answers without writing a single line of SQL.
Every engagement is quoted individually, based on its scope, complexity, and delivery needs. We agree on the work and its cost before development begins.
For bespoke projects, you own the custom code, with client-controlled repositories and infrastructure, documentation, and a complete handover. Third-party components and services retain their own licenses and terms. When an existing product fits your needs, I can help you adopt and configure it, avoiding unnecessary development. You receive access under that product's agreed terms; its underlying platform remains with its owner.
One-off projects include 60 days of bug fixing and stabilization after launch for the agreed delivery. Continued support can follow through a maintenance agreement, with additional features scoped separately. Existing-product access follows that product's support terms.
Tell me about the idea, the problem, or the part of your product you want to move forward. We can work out the scope and the right next step together.
Let's talk about your product