Senior Software Engineer

Microsoft Microsoft · Big Tech · Vancouver, BC +2 · Software Engineering

Senior Software Engineer role on the Azure Data engineering team, focusing on data integration products like Azure Data Factory and Power Query. The team builds data infrastructure for millions of users on the Microsoft Fabric platform and is enhancing existing platforms to support AI copilots and large-scale data analytics. Responsibilities include developing and operating backend services, partnering with PMs, driving technical decisions, writing code, troubleshooting production issues, and mentoring peers.

What you'd actually do

  1. Develop and operate highly reliable, scalable backend services and data platforms
  2. Partner with PMs and engineers to define requirements and design solutions for new product capabilities.
  3. Drive design discussions and own key technical decisions across components and services.
  4. Write clean, secure, and maintainable code with strong test coverage and performance considerations.
  5. Troubleshoot production issues using telemetry and debugging tools, and drive root-cause analysis.

Skills

Required

  • Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Nice to have

  • Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
  • Strong backend engineering experience (distributed systems, reliability, performance)
  • Proficient in C# and familiar with the Microsoft ecosystem (Azure, .NET)
  • Experience with data systems, ETL pipelines, and large-scale data processing
  • Familiarity with Databricks, Spark, or similar big data tools

What the JD emphasized

  • data integration infrastructure
  • large-scale data analytics
  • AI copilots