Sync engineering work data from Jira into Snowflake automatically. Stop exporting CSVs, building fragile ETL scripts, or waiting on data teams to update sprint metrics. Redbird keeps your issue tracking data warehouse-ready in real time.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Automatically stream issue creations, status changes, assignee updates, and sprint transitions from Jira into structured Snowflake tables. Keep engineering activity data current for dashboards and cross-functional reporting without manual exports or cron jobs.
Capture issue lifecycle events with timestamps as they happen in Jira and warehouse them in Snowflake. Enable data teams to run retrospective analyses on sprint velocity, lead time, and throughput trends across quarters without piecing together exports.
Pull customer tier, ARR, and account health scores from your Snowflake data warehouse and append them to Jira issues. Help engineering teams prioritize bugs and features based on customer impact metrics that live in your analytics layer.
Automatically join sprint completion data from Jira with revenue, deployment frequency, and incident metrics stored in Snowflake. Produce comprehensive engineering performance reports that connect delivery output to business outcomes.
Query Snowflake for trends like rising bug counts, prolonged cycle times, or sprint carryover rates calculated from historical Jira data. Trigger notifications when thresholds are crossed so teams can intervene before milestones slip.
Combine Jira workload data with employee records, team structures, and allocation models in Snowflake. Create up-to-date capacity planning tables that inform resourcing decisions based on actual issue throughput and assignment patterns.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Jira and Snowflake with OAuth or API credentials. Redbird never stores your data — it just passes through.
Tell Redbird what to do in plain language — no SQL, no code, no configuration files required.
Redbird shows you exactly what it will do before running anything. Approve the workflow, set a schedule, and switch it on.
Workflows run on your schedule or on triggers. Every run is logged. Adjust with natural language at any time.
Redbird understands Jira's issue schemas, custom fields, and workflow states alongside Snowflake's table structures and data types—no manual mapping required.
Redbird automatically detects Jira custom fields, issue type hierarchies, sprint cadences, and workflow transitions. It translates them into clean, normalized Snowflake tables with proper types—parsing dates, JSON fields, and relational links between issues, epics, and sprints. The AI handles schema drift when you add custom fields or change workflows, updating your warehouse structure without breaking downstream queries.
faster than building custom ETL pipelines for Jira data
Redbird can pull from Jira and Snowflake simultaneously, merge the results, and format a polished report — sent on a schedule or on demand.
Set conditions in natural language. Get notified in Slack or email the moment a threshold is crossed in either Jira or Snowflake.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from Jira into Snowflake, or from Snowflake back into Jira. Resolve conflicts with configurable merge rules.
Every workflow run is logged — what ran, what changed, and why. Replay or revert any individual step at any time.
Start workflows from any issue event in Jira or query result in Snowflake—Redbird handles the sync and orchestration.
Fires when any issue is created, edited, reassigned, or transitioned between workflow states.
Triggers when a sprint begins, closes, or has its scope changed.
Detects when an issue moves to a specific status like 'In Review', 'Done', or custom workflow states.
Generate new Jira issues or modify existing ones with field updates based on external data.
Post AI-generated insights or data summaries as comments on specific issues.
Write enriched data from Snowflake into Jira custom fields like priority scores or customer impact ratings.
Fires when a scheduled Snowflake query result meets specified conditions or exceeds limits.
Detects when fresh data arrives in specified Snowflake tables via ETL processes or data shares.
Triggers when a time-based analytical query completes and results are materialized.
Write Jira issue data into Snowflake tables with proper typing and incremental updates.
Run complex SQL against warehouse data to generate metrics, aggregations, or joined datasets.
Build optimized views from Jira data for faster BI tool performance and analyst access.
Sync Jira with Snowflake in minutes. Give your data team direct access to engineering metrics and your dev team visibility into business context—without building pipelines.