DATA OPS

Reverse-ETL Freshness Guard: Snowflake to HubSpot with PagerDuty Escalation

Monitors Snowflake-to-HubSpot sync freshness and escalates to PagerDuty when lag crosses a critical SLA, while routine warnings stay in Slack.

CategoryData Ops
Enginesim
Difficultyadvanced
Triggerschedule
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerEvery 15 minutes (schedule)
  • ActionQuery Snowflake ETL metadata for last load timesSnowflakeSnowflake
  • LogicClassify each model: healthy / warning / critical
  • ActionPost warning-level lag to SlackSlack
  • ActionOpen PagerDuty incident for critical SLA breachPagerDutyPagerDuty
  • OutputAnnotate affected HubSpot record count on the alertHubSpotHubSpot

What it does

This workflow guards the Snowflake models feeding HubSpot marketing and CRM properties. It measures sync lag on a schedule and applies two-tier severity: minor lag posts a Slack warning, but lag past the hard SLA opens a PagerDuty incident so the on-call data engineer is paged.

When to use it

Use it when stale HubSpot data has real cost — misfired campaigns, wrong lifecycle stages, bad segmentation — and you need paging, not just a chat ping, once freshness breaches your SLA.

How it works

  1. 1A schedule runs every 15 minutes.
  2. 2A Snowflake query returns each synced model's latest load timestamp from your ETL metadata table.
  3. 3A logic step classifies each model as healthy, warning, or critical against its SLA.
  4. 4Warning-level lag posts a non-paging Slack notice.
  5. 5Critical-level lag triggers a PagerDuty incident with the model name, lag, and affected HubSpot objects.
  6. 6A final HubSpot check annotates how many records depend on the stalled model so responders know blast radius.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect SnowflakeWarehouses, queries, shares.
  2. 2
    Connect HubSpotCRM, deals, marketing, support.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Connect PagerDutyIncidents, on-call, escalations.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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