Senior Data Reliability Engineer

Responsibilities

• Design and implement end-to-end data observability across pipelines and data platforms, covering the core data quality pillars: freshness, volume, schema, completeness and accuracy
• Embed automated data quality checks into CI/CD pipelines and orchestrators (e.g., dbt tests, Great Expectations, native platform checks)
• Configure anomaly detection — including dynamic and ML-based thresholds — for data drift, volume anomalies and pipeline failures
• Define, measure and report Data SLIs, SLOs and error budgets together with business and data product stakeholders
• Perform root cause analysis by tracing data lineage upstream to the exact origin of a failure; drive problem management so incidents do not recur
• Design architectural guardrails for data pipelines: circuit breakers, dead-letter queues, retry and rollback mechanisms, self-healing patterns
• Implement monitoring and alerting as code (Terraform / GitOps) instead of manual UI configuration
• Reduce alert noise through event correlation, tagging standards and actionable alert design
• Build reusable data quality and observability frameworks, templates and accelerators adopted by multiple data product teams
• Lead post-incident reviews and translate learnings into systemic platform improvements

Languages