Sync your engineering data from Jira directly into BigQuery for analysis, or push data warehouse insights back into tickets. Stop exporting CSVs, writing custom API scripts, or waiting for manual reports to understand team velocity and project health.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Automatically capture sprint completion data, story points, cycle times, and team assignments from Jira into BigQuery tables. Join engineering metrics with product analytics, revenue data, and customer usage to understand development ROI. Build executive dashboards that connect engineering output to business outcomes.
Run scheduled SQL queries in BigQuery to detect errors, performance degradations, or data quality issues. Automatically create Jira bugs with context from the warehouse — including affected tables, error counts, and severity. Assign tickets based on data ownership metadata stored in BigQuery.
Sync closed issues, historical sprint data, and project metadata from Jira into BigQuery on a scheduled basis. Maintain unlimited history for trend analysis without hitting Jira's performance limits. Enable year-over-year engineering analytics and retrospective planning based on complete historical context.
When high-priority bugs are created, query BigQuery to determine how many users are affected, revenue at risk, and which enterprise customers are impacted. Automatically add custom field data to Jira tickets so engineers can prioritize with business context. Surface warehouse insights directly in the development workflow.
Schedule BigQuery queries that calculate deployment frequency, lead time, DORA metrics, and technical debt trends. Create or update Jira dashboard cards and comments with the latest metrics. Keep engineering leadership informed without requiring SQL knowledge or warehouse access.
Stream Jira ticket transitions, assignee changes, and priority updates into BigQuery as they happen. Enable real-time dashboards showing what's in code review, blocked, or ready for QA. Combine with deployment data and observability metrics for complete SDLC visibility in your warehouse.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize BigQuery and Jira 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 both BigQuery's nested table schemas and Jira's complex issue hierarchies, so you can connect engineering workflows to your data warehouse without custom code.
Redbird maps Jira's nested JSON fields — custom fields, issue links, sprint objects, and changelog history — to clean BigQuery tables automatically. It handles schema evolution as you add custom fields or change project configurations. When pushing data back to Jira, Redbird validates field types, required attributes, and project-specific schemas so updates never fail. The AI understands time-series patterns in both systems, properly handling sprint boundaries, issue transitions, and historical snapshots.
faster than building custom Jira-to-BigQuery ETL pipelines
Redbird can pull from BigQuery and Jira 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 BigQuery or Jira.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from BigQuery into Jira, or from Jira back into BigQuery. 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 query results in BigQuery or project changes in Jira — Redbird handles the rest.
Trigger when a scheduled or streaming SQL query in BigQuery returns rows meeting specified conditions.
Detect when new data is inserted, updated, or deleted in specified BigQuery tables or datasets.
Fire when ML models or statistical thresholds identify unusual patterns in BigQuery data.
Write new records from Jira into BigQuery tables with automatic schema mapping and type conversion.
Execute SQL queries in BigQuery using dynamic values from Jira tickets or workflow context.
Modify existing BigQuery rows based on Jira issue changes or calculated values from other systems.
Trigger when Jira tickets move to specific statuses like Done, In Review, or Blocked.
Fire when a sprint closes in Jira, capturing all associated issues and metrics for analysis.
Detect when new bugs or tasks above a certain priority threshold are added to specified projects.
Generate new Jira tickets with descriptions, custom fields, and attachments populated from BigQuery data.
Modify Jira ticket priority, labels, custom fields, or story points based on warehouse insights.
Post automated comments to Jira tickets with analysis results, metrics, or alerts from BigQuery queries.
Stop building custom scripts to sync Jira and BigQuery. Connect your engineering tools to your data warehouse in minutes and start automating analytics workflows today.