At Microsoft, our mission is to empower every person and every organization on the planet to achieve more. For decades Microsoft Azure has democratized computing and made it possible for billions of humans everywhere to achieve more! This is a very exciting time to be at Microsoft and be part of Azure.
The Fundamentals Data Engineering & Intelligence Team has an immediate opening for a highly motivated Software Engineer who is curious, loves solving data engineering challenges at all levels of the stack, and is very passionate about deriving insights leveraging their skills in, but not limited to, software engineering, data analysis, and AI/ML.
Our organization delivers the OS and/or components for Linux and Windows, both in the cloud and at the edge. Our Data Engineering and Intelligence Team works closely with Program Management to define customer scenarios and determine what measurements, metrics, and insights are required to understand our customers' interactions with our software and assess our business and engineering goals. We use software engineering techniques, data engineering, data science, and data analytics methods to measure and assess the quality of our products, our users' level of engagement and interaction with our features, and our customers' sentiment towards our products. Our Software Engineers are knowledgeable in traditional Computer Science, Data Engineering, Data Science, Machine Learning, and Big Data. We work with new and existing telemetry systems to collect and process large amounts of data that we then turn into actionable insights to support fact-based and data-driven decisions.
• 5+ years of software design and development experience in an object-oriented language (e.g., C/C++, C#) and/or a scripting language (e.g., Python).
• 2+ years of experience working with large-scale computing systems like COSMOS, Geneva, U-SQL, Spark, HDInsight, Hadoop, MapReduce, and/or similar systems.
• 2+ years of experience working with relational databases using structured query languages like SQL.
• Ability to deliver results while working on loosely defined projects with incomplete data sets.
• Strong hands-on experience in decision sciences, machine learning, and data mining.
• Excellent written and verbal communication skills.
• Excellent interpersonal skills.
• Deep familiarity with statistical models and methods (time-series analysis, regression analysis, experimental design, hypothesis testing, etc.)
• Ability to persuade strong personalities with hard data and facts, the ability to communicate complicated analysis methods, and the ability to explain technical insights to non-technical audiences.
• Focus on statistics, probability, big data, or machine learning.
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Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
• Discover and present key insights that impact and help define product development.
• Analyze multiple large data sets using data science methods and scientific experimentation.
• Develop models of product usage and user behavior from telemetry data.
• Write telemetry instrumentation code in both Windows and Linux environments.
• Work with multiple feature teams in all disciplines to both produce and consume shared data assets.
• Use your creativity to solve complex data engineering challenges.
• Provide actionable recommendations that bring business value and improve our products.
• For V1 products, create test suites that validate customer scenarios.
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