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Senior Data Engineer
Job
Microsoft
Redmond, WA (In Person)
Full-Time
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Job Description
Design, build, and maintain scalable, reliable data pipelines that ingest, transform, and serve Excel product telemetry and related datasets. Partner with Product Managers and Software Engineers to define telemetry requirements and ensure instrumentation supports clear product questions and success metrics. Own data modeling and transformation logic that turns raw event data into well-structured, analytics-ready datasets. Ensure data quality, correctness, and reliability through validation, monitoring, and proactive issue detection across pipelines. Collaborate closely with Data Analysts, Data Scientists and partner teams to enable efficient analysis, experimentation, and AI/ML workflows. Build and maintain monitoring, alerting, and documentation so data pipelines are observable, trustworthy, and easy to operate. Anticipate and address data governance, privacy, and compliance requirements, ensuring data is handled and accessed appropriately. Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 3+ years experience in business analytics, data science, software development, data modeling, or data engineering OR Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+ years experience in business analytics, data science, software development, data modeling, or data engineering OR equivalent experience. These requirements include but are not limited to the following specialized security screenings: 4+ years of experience working as a Data Engineer, Software Engineer (data-focused), or in a similar role building production data systems. Strong experience designing and operating data pipelines for large-scale, product or telemetry data. Proficiency with SQL and at least one general-purpose programming language such as Python, C#, or Scala. Experience with data modeling, ETL/ELT workflows, and building analytics-ready datasets. Hands-on experience ensuring data quality, reliability, and pipeline observability. Ability to work cross-functionally and communicate clearly with both technical and non-technical partners. Experience supporting experimentation platforms or metrics frameworks. Experience enabling AI/ML workflows in product environments. Exposure to privacy‑ and compliance‑aware data systems at global scale. Demonstrated ability to influence product decisions through data design.