Data Engineering · System Integration
Data as infrastructure. Systems that work together by design.
We design and build data platforms that reflect how the business actually operates: one set of shared, trusted data that supports reporting, analytics, and whatever AI work comes next. It's more than dashboards or pipelines. It's treating data like infrastructure, something the rest of the organization can build on without double-checking it first.
Data Engineering
We build modern data platforms on the Microsoft stack, structured in a medallion architecture so raw, refined, and business-ready data are clearly separated, governed, and trustworthy. Reporting and analytics run on one dependable foundation instead of a tangle of competing spreadsheets and one-off extracts.
System Integration
As organizations grow, integrations become structural, not optional. We design integration patterns that align systems around the business architecture, reducing manual work, rework, and failure points. The result is systems that actually talk to each other, instead of quietly failing at 2am and someone finding out three days later.
Real time when the business needs it
Not every decision can wait for tonight's batch. We design event-driven integration that moves data the moment it changes, so operational reporting reflects reality instead of yesterday's version of it.
What that actually looked like
A client needed data in Power BI within five minutes of entry in Dynamics 365 Finance & Operations. We streamed F&O events to Service Bus, updated the target rows in Azure SQL, and served an optimized DirectQuery report, replacing a slow batch refresh with a design that met the five-minute service level.
On another engagement we rebuilt a Dynamics 365 F&O analytics pipeline on Microsoft Fabric using Python and Spark SQL, cutting processing time from 1.5 hours to 35 minutes, roughly 61 percent faster. On a third, we built a system that queried a DB2/400 database from Azure in real time, as packages were being picked, packed, and shipped, on a decommissioned, technically out-of-service IBM AS/400 that nobody expected to still be doing real work. It was.
From fragmentation to a single, trusted foundation
We've consolidated hundreds of supply chain applications into unified platforms, aggregated data from many third-party logistics partners into linked Cosmos DB, Azure SQL, and Blob Storage so a global organization could satisfy government audits worldwide, and connected on-premises systems to the cloud over private ExpressRoute links. The pattern is consistent: align the data and integration to the business architecture, then let the systems evolve without destabilizing operations.