Software Quality Engineering Ic1

Microsoft Microsoft · Big Tech · IL · Software Quality Engineering

The Azure Data engineering team is building the data platform for the age of AI, powering a new class of data-first applications. This role focuses on ensuring the quality, reliability, and performance of a highly integrated, end-to-end analytics ecosystem within the Microsoft Fabric platform. The team uses a shift-left approach, building intelligent automation, leveraging telemetry, and validating customer workflows in a cloud-native environment. The Software Test Engineer will develop scalable test frameworks, ensure interoperability across Fabric workloads, and identify systemic quality risks.

What you'd actually do

  1. Design and implement scalable test strategies and automation that validate end-to-end scenarios across the Fabric Platform, with emphasis on cross-workload integration and real-world usage patterns.
  2. Build and evolve intelligent test infrastructure that leverages telemetry, synthetic data, and production signals to detect issues before they impact customers.
  3. Identify systemic quality risks across services and drive improvements in reliability, performance, and resilience at cloud scale.
  4. Contribute to a culture of continuous quality by improving test coverage, reducing gaps, and enabling faster, more confident delivery.
  5. Investigate complex issues in distributed systems, using data-driven approaches to isolate root causes and validate fixes effectively.

Skills

Required

  • Software test strategy design and implementation
  • Test automation development
  • End-to-end scenario validation
  • Cross-workload integration testing
  • Intelligent test infrastructure development
  • Telemetry and production signal utilization
  • Synthetic data generation and utilization
  • Systemic quality risk identification
  • Reliability, performance, and resilience testing
  • Distributed systems debugging
  • Data-driven root cause analysis

Nice to have

  • Cloud-native environment experience
  • Experience with Microsoft Fabric platform
  • Experience with Azure data services (SQL DB, Cosmos DB, Data Factory, Synapse Analytics, etc.)
  • Knowledge of data ingestion, transformation, and governance

What the JD emphasized

  • validate end-to-end scenarios across the Fabric Platform, with emphasis on cross-workload integration and real-world usage patterns
  • intelligent test infrastructure that leverages telemetry, synthetic data, and production signals
  • systemic quality risks across services
  • complex issues in distributed systems