Data Observability Engineer

XpertDirect; Zürich; Vor Ort; CHF 100.000 - 150.000; Vollzeit

Zusammenfassung

XpertDirect in Zurich, Switzerland, seeks a Data Observability Engineer to build systems that detect broken pipelines, data-quality degradation, lineage issues, and production failures before they affect downstream teams and products.

You will work at the intersection of Data Engineering, Observability, and Reliability Engineering, creating visibility across the complete lifecycle of production data.

Qualifikationen

• 3+ years in Data Engineering, Data Platform Engineering, Data Reliability, or similar roles.
• OpenTelemetry or comparable observability technologies.
• Data-quality monitoring.
• Strong understanding of modern production data pipelines.
• Nice-to-have: Monte Carlo or Bigeye data-observability tooling.

Aufgaben

• Build observability systems for production data pipelines.
• Develop automated data-quality checks and monitoring in Python and SQL.
• Monitor Airflow pipelines for failures, delays, and abnormal behaviour.
• Build observability across Snowflake data workloads.
• Integrate quality and reliability checks into dbt workflows.
• Develop telemetry and tracing using OpenTelemetry.
• Detect schema changes, freshness issues, and data-quality degradation.
• Improve visibility into data lineage and upstream/downstream dependencies.
• Define SLIs and reliability standards for critical data products.
• Build alerting and automated diagnostics for production data incidents.
• Perform root-cause analysis across complex data pipelines.
• Partner with Data Engineers to embed reliability in platform design.

Kenntnisse

Data Engineering

OpenTelemetry

Data quality monitoring

Data pipelines

Tools

Monte Carlo

Bigeye

Jobbeschreibung

Data Infrastructure | Data Observability | Data Reliability | Data Quality | Data Engineering

Our client, a growing Data Infrastructure company based in Zurich, is looking for a Data Observability Engineer to build the systems that detect broken pipelines, data-quality degradation, lineage issues, and production failures before they affect downstream teams and products.

You'll work at the intersection of Data Engineering, Observability, and Reliability Engineering, creating visibility across the complete lifecycle of production data.

What You’ll Work On

• Build observability systems for production data pipelines
• Develop automated data-quality checks and monitoring in Python and SQL
• Monitor Airflow pipelines for failures, delays, and abnormal behaviour Build observability across Snowflake data workloads
• Integrate quality and reliability checks into dbt workflows
• Develop telemetry and tracing using OpenTelemetry
• Detect schema changes, freshness issues, volume anomalies, and data-quality degradation
• Improve visibility into data lineage and upstream/downstream dependencies
• Define SLIs and reliability standards for critical data products
• Build alerting and automated diagnostics for production data incidents
• Perform root-cause analysis across complex data pipelines
• Partner with Data Engineers to make reliability and observability part of platform design

Core Skills

• 3+ years in Data Engineering, Data Platform Engineering, Data Reliability, or similar roles
• OpenTelemetry or comparable observability technologies
• Data-quality monitoring
• Strong understanding of modern production data pipelines

Nice to Have

• Monte Carlo / Bigeye or similar data-observability tooling
• Incident management and postmortems