A reliable, right-sized reference build. The same patterns we ran at scale, trimmed down to what a startup actually needs and can keep running.
Data goes from your sources to numbers people trust, watched the whole way, so a failure gets caught and re-run instead of surfacing in a board deck.
Figure 1 — A reliable, right-sized stack. The dashed layers, orchestration and monitoring, are what turn a pile of jobs into something you can trust.
Your production database, SaaS tools, and product events — wherever the data already lives.
Data lands raw and untouched, on a schedule, so a transform bug never costs you the original.
An immutable landing zone — cheap, and your replay button when something needs reprocessing.
dbt models, version-controlled and tested, promote raw data into clean, business-ready tables.
Modeled tables land in the warehouse for fast queries your dashboards and analysts hit.
BI, metrics, and ML features draw only from governed, validated data — never the raw mess.
Every job is safe to re-run, retries when something flakes, supports backfills, and pings a human when it can't recover. This is the part we're best at. It's the difference between "the pipeline ran" and "the pipeline ran correctly."
Data-quality checks, freshness SLAs, and lineage turn a silent failure into a loud alert. You hear that a number's wrong from a monitor, not from a confused board member.
Plenty of teams don't need a rebuild. They need what's already there to stop falling over.
Picture a Series-A SaaS team with data in Postgres, Stripe, and Segment, stitched together by cron jobs a founding engineer wrote at 1am. Jobs fail quietly, fire in the wrong order, and can't be safely re-run. So every metric comes with a quiet "probably." The fix isn't fancier tools. It's making the whole thing reliable.
Figure 2 — Same data, made reliable. Orchestrated, monitored, re-runnable, and no rip-and-replace.
No more silent failures or 1am firefighting. Jobs run in order, recover on their own, and page someone when they can't. The numbers stop coming with an asterisk.
A handful of well-built, monitored jobs. Not a platform team's worth of infrastructure. Reliable enough to trust, simple enough for your team to keep running.
Want this for your stack? Start with an audit — a short, fixed-scope look at what's breaking and what to fix first. Email us or see services.
