A Data Pipeline Observability And Reliability Framework For Enterprise Insurance Systems: Real-Time Health Monitoring, Data Quality, And Automated Alerting At Scale

Abstract

Enterprise insurance data platforms move large volumes of sensitive data across many systems on fixed schedules, and the monitoring that watches them almost always watches execution status. Execution status answers whether a job ran. It does not answer whether the data that job produced is complete, current, correctly shaped or safe to publish. A pipeline can finish with a success code while loading a partial file, reprocessing stale source data, duplicating records, or silently dropping a column that an upstream system renamed, and every one of those outcomes reaches downstream reporting with no alert attached to it. This paper presents an observability and reliability framework that treats operational health and data quality as two signal families that must be evaluated together and reduced to a single health score per pipeline. The framework covers ingestion-time validation before processing begins, execution monitoring against historical baselines rather than static thresholds, staged data quality assessment returning pass, warning or fail, metadata and lineage capture for impact analysis, health scoring, and severity-based alert routing with deduplication and correlation. The work is grounded in a production deployment in an enterprise insurance data environment between July 2025 and July 2026, in which a centralised dashboard monitored approximately 12,500 scheduled jobs at an approximately one-minute refresh interval, reduced manual monitoring effort by approximately two to four hours per engineer per day, and made failures and delays visible within one to five minutes of a status change against several hours under manual checking. Those four outcomes are measured. The wider architecture described here, including standardised quality monitoring, health scoring, and the alerting policy, is generalised from that deployment and has not been formally evaluated; its expected benefits are stated as design targets and labelled as such throughout. Section VIII draws the boundary explicitly, and the paper claims no figure that was not recorded.