Data Platforms & Integration
Systems that agree with each other.
Half-finished platforms tend to leave data stranded: partial migrations, brittle integrations, reports nobody trusts. We finish the pipelines, reconcile the systems, and make the numbers dependable.
We work in whatever the project already uses: its language, its framework, its cloud. Taking over a build means adopting the decisions already made, not restarting on ours.
The signals that bring this work to us
If more than one of these sounds familiar, an assessment is usually the cheapest next step. It replaces guesswork with a scoped plan.
A migration that was started and never completed, leaving two sources of truth
Integrations that break quietly and are discovered days later
Reporting that different teams calculate differently
Batch jobs that no longer finish inside their window
Concrete work, not a capability list
Data Migration & Backfill
Migrations completed with verification, reconciliation, and a documented cutover rather than an open-ended parallel run.
System Integration
Reliable interfaces between internal services and third-party platforms, with retries and failure visibility.
Pipelines & Warehousing
Ingestion and transformation pipelines feeding a warehouse your reporting can actually rely on.
Data Quality Controls
Validation, schema enforcement, and alerting so bad data is caught at the boundary.
Query & Storage Tuning
Indexing, partitioning, and query work to bring slow reads back within budget.