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Managed DataOps — Active

Your pipelines.
Our problem.

Pipeline manages your dbt jobs, Airflow DAGs, and Snowflake costs so your engineering team stops firefighting schema drift at 2 AM and starts shipping product.

dbt Core & CloudApache AirflowSnowflakeFivetranBigQuery
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Customer
Customer
Customer
140+ engineering teams sleeping through the night
pipeline.yml — prod-warehouse-sync
LIVE
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pipeline:
name: "prod-warehouse-sync"
version: 3.1.4
schedule: "*/15 * * * *" # every 15 min
sources:
fivetran:
connector: salesforce_prod
schema_drift: auto_handle # ⚠ schema change detected → auto-handled
on_failure: retry(3) # no page-out
transforms:
dbt:
models: [fct_revenue, dim_customers]
freshness_sla: 900 # seconds
cost_guard: enabled # ⚠ cost anomaly → throttled before your CFO notices
warehouse:
snowflake:
cluster_auto_suspend: 60
query_governance: strict # runaway queries blocked
monitoring:
status: ✓ healthy # pipeline.so/status/prod
oncall_pages_today: 0 # you slept through the night
dbt Job MonitoringAirflow OrchestrationSchema Drift PreventionSnowflake FinOpsFivetran Sync ManagementIncident ResponseZero On-Call PagesPipeline Migrationdbt Job MonitoringAirflow OrchestrationSchema Drift PreventionSnowflake FinOpsFivetran Sync ManagementIncident ResponseZero On-Call PagesPipeline Migration
99.97%Pipeline Uptimeacross all managed jobs
< 4 minMean Time to Resolvevs. 47 min industry avg
2,840+Schema Drifts Caughtbefore they hit production
$2.1MSnowflake Costs Savedfor clients YTD 2025
Capability Comparison

Every capability.
Zero overhead.

Observability
Pipeline Monitoring
Expand →
Time Spent
12 hrs/wk
Tooling
Datadog + PagerDuty + custom scripts
Incidents
8–14 pages/month

Alert fatigue. Engineers context-switch mid-sprint.

Scheduling
Airflow Orchestration
Expand →
Time Spent
8 hrs/wk
Tooling
Self-hosted Airflow + Kubernetes + ops rotation
Incidents
4–6 DAG failures/week

DAG debugging consumes senior eng time. Infra drift.

Data Quality
Schema Drift Management
Expand →
Time Spent
6 hrs/wk
Tooling
Great Expectations + manual contracts + Slack alerts
Incidents
2–4 silent corruption events/quarter

Schema breaks surface 24h late. Stakeholders lose trust.

FinOps
Snowflake Cost Optimization
Expand →
Time Spent
5 hrs/wk
Tooling
SELECT * from QUERY_HISTORY + spreadsheets
Incidents
$4k–$18k monthly overruns typical

CFO asks questions. Nobody has answers until the bill arrives.

Reliability
Incident Response
Expand →
Time Spent
10 hrs/wk
Tooling
Runbooks + PagerDuty + tribal knowledge
Incidents
47 min avg MTTR

Institutional knowledge walks out the door when eng leaves.

Final row: the math is simple
Your in-house stack costs more than you think. Run the numbers.
Run the Cost Comparison →
ROI Calculator

Run your numbers.
Then decide.

Three inputs. Instant projection. No sales call required to see if Pipeline makes financial sense for your team.

Your Current State
$

Find this in your Snowflake billing dashboard

Including contractors and embedded data eng

Slack alerts, Fivetran failures, DAG retries

Fill in the three fields to see your projected annual savings

Awaiting input →

Projections based on median outcomes across 140+ Pipeline clients. Actual savings vary by stack complexity and incident baseline.

From the Trenches

Engineering leaders
who stopped paging.

0on-call pages in 90 days
"We had three data engineers spending 40% of their time on pipeline babysitting. Pipeline took that off their plate entirely. They shipped our real-time inventory system in the time we used to spend fighting Fivetran."
Priya Nair, VP Engineering
Priya Nair
VP Engineering
Meridian Analytics — Series C, $42M raised
$11kmonthly Snowflake reduction
"I was skeptical that a managed service could handle our Snowflake complexity — we had 80+ dbt models and some deeply cursed macros. Pipeline had it documented and monitored in two weeks. Our Snowflake bill dropped $11k/month."
James Okafor, CTO
James Okafor
CTO
Veritas Growth — Series D, $120M raised
2 FTEequivalent capacity reclaimed
"The thing nobody tells you about building a data platform team is how much of your senior eng time gets eaten by toil. Pipeline gave us back two senior engineers worth of capacity without adding headcount."
Aisha Kamau, VP Engineering
Aisha Kamau
VP Engineering
Northgate Data — Mid-market, 600 employees
Ready When You Are

The next time your pipeline
breaks at 3 AM
it won't be your problem.

Book a 45-minute technical audit. We'll review your stack, identify your top failure points, and show you exactly what Pipeline takes off your plate.

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No commitment · 45 minutes · Bring your Snowflake bill