We architect resilient distributed data pipelines, modern analytical warehouses, and automated real-time transformation streams that turn complex metrics into actionable insights.
4.2B
events processed daily across client stacks
SELECT insight,
action
FROM raw_noise
WHERE signal = true;
— the whole job, honestly
4.2B
Events / Day
38%
Avg. Warehouse Cost Cut
120+
Pipelines Shipped
<2h
Reply SLA
Fixed-scope engagements for teams drowning in brittle ETL, stale warehouses, and dashboards nobody trusts. Pick a card, send the brief, get a timeline.
A blunt teardown of your ingest, transform, and serving layers — what breaks first, what costs most, and what to fix this quarter.
A version-controlled dbt project with tested, documented models your analysts can finally trust without a Slack caveat.
Move off the legacy warehouse or raw S3 lake onto Snowflake, BigQuery, or Redshift — with zero reporting downtime during cutover.
Kafka-based event backbone with exactly-once sinks feeding live dashboards, alerting, and downstream services.
Retire brittle cron scripts and midnight CSV drops in favor of orchestrated, observable, retried DAGs.
Three executive dashboards in Looker Studio, Power BI, or Metabase — built on certified models, not spreadsheet duct tape.
Freshness, volume, and schema checks that page the right human before your stakeholders spot the wrong number.
Batch and near-real-time feature pipelines with point-in-time correctness, so training and serving finally agree.
A query, clustering, and warehouse-size audit that typically pays for itself in the first billing cycle.
A named engineer keeps your DAGs, tests, and warehouses healthy — with a guaranteed reply window, not a ticket void.
Send the brief and get a fixed scope, a delivery window, and a named engineer — usually within two business hours.