Build and maintain observability across enterprise data pipelines by implementing data quality, freshness, volume, and schema monitoring. Configure tooling such as Monte Carlo, Great Expectations, CloudWatch, and Datadog; create alerts, maintain SLAs and runbooks, and perform incident triage and root cause analysis. The role requires AWS data services, Python, SQL, and data quality framework expertise.
Implement monitoring and observability across enterprise data pipelines to ensure reliability and data trust.
- Build data quality checks, freshness/volume/schema monitoring and alerting
- Set up observability tooling (e.g., Monte Carlo, Great Expectations, CloudWatch, Datadog)
- Perform incident triage and root cause analysis; maintain SLAs and runbooks
Requirements
- Must have: 4+ yrs, AWS (Glue, S3, Lambda, Redshift, CloudWatch), Python, SQL, data quality frameworks
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