CI/CD for a Data Engineering Team

Data CI runs dbt models, pipeline tests, and warehouse checks - long, heavy jobs where a transient warehouse blip fails the run.

Data engineering CI tests transformations and pipelines against real systems. Jobs are heavy and exposed to transient connection and warehouse failures.

Heavy, integration-bound jobs

dbt builds and pipeline tests run against warehouses and external systems, so runs are long and exposed to transient network/warehouse errors.

Auto-retry transient failures

Self-healing retries transient connection drops and warehouse 5xx so a one-off blip does not fail a long data run.

Cache and parallelize

Cache Python/dbt environments and shard model tests so the suite finishes faster as the project grows.

Cost of long runs

Long, frequent data jobs add up. Managed runners at about 69 percent lower cost keep the data CI bill in check.

Key takeaways

• Data jobs are long and integration-bound.
• Auto-retry transient warehouse/network failures.
• Cache, shard, and run about 69 percent cheaper.

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