We are looking to hire a Data Science Engineer to join our team. As part of Microsoft Azure, the Azure Networking team designs and builds the network infrastructure that powers hundreds of thousands of servers in datacenters around the globe, providing network infrastructure services for Azure, Bing, and other Microsoft cloud services. In Azure Networking, we are at the very front of Cloud Computing by running one of the largest data center network infrastructures in the world. Our team is responsible for ensuring the reliability of these networks, even in the face of constant change. We rely on cutting edge network architecture and design for this purpose.
Are you a data enthusiast with a knack for engineering and analytics? Are you able to analyze trends across millions of Devices and links around the world? If you have a penchant for measuring, understanding, and visualizing real-world link and device data to derive insights that drive business metrics, we are eager to connect with you!
As part of Microsoft Azure, the Azure Networking team designs and builds the network infrastructure that powers hundreds of thousands of servers in data centers around the globe, providing core network infrastructure services for Azure, Bing, and other Microsoft cloud services. In Azure Networking, we are at the very front of Cloud Computing by running one of the largest data center network infrastructures in the world. By joining this team, you will gain marketable experience in service-oriented network architectures and data center networking at massive scale.
We need people to analyze worldwide data network performance and trends across data centers and azure regions. This role is focused on making sure links and devices in service are operating well, and that links and devices out of service will not cause capacity or planning problems. This role requires working across multiple teams and business priorities.
This role also working with third party vendors and tracking mtbf’s and issues across device generations.
We value creativity and innovation and encourage a culture of fast experimentation and iteration. Join us in our journey to track and improve the reliability of Azure Data Networking.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

REQUIRED QUALIFICATIONS:

• Bachelor’s Degree in Computer Science, or related field
• OR equivalent experience.

OTHER REQUIREMENTS:

• Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:
• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.

PREFERRED QUALIFICATIONS:

• Bachelor’s Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 1+ year(s) experience in business analytics, data science, data modeling or data engineering work
• OR Master’s Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field
• OR equivalent experience.
• Experience with Azure services and administration thereof
• Experience with Data Networking and large scale ethernet networks
• Experience in designing/implementing large-scale data infrastructure to support a Data Science team
• Ability to write code in a variety of programming/scripting languages such as Python, C++/C#, Java and/or PowerShell, etc.
• Familiarity with relational databases
• Working knowledge of a variety of big data sources in Kusto,Spark, Scala, and/or other big data systems
• Bachelor’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
• OR equivalent experience
• Experience in a Data Engineer or Software Engineer role with a focus on cloud-based big data processing
• Experience in developing tools and data pipelines using Azure Data Factory, Synapse, Apache Spark or similar tools
• Experience in building and optimizing “big data” workflows using modern cloud-based platforms, including ETL
• Experience in supporting business intelligence data pipelines, serving data exploration and visualization tools like Azure Data Explorer and Power BI
• Understanding of data modeling and data architecture design patterns
  Data Engineering IC2 - The typical base pay range for this role across the U.S. is USD $81,900 - $160,200 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $105,600 - $174,600 per year.
  Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay
  Microsoft will accept applications for the role until July 7, 2024.
  

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Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

• Design and develop distributed cloud-scale data pipelines and software services that are engineered for scale, availability, high performance, and high reliability.
• Own and deliver complete features including design, architecture, implementation, testability, debugging, and shipping.
• Collaborate with internal partner teams and external customer teams to drive key platform insights and innovate scenarios to support new capabilities.
• Advocate for best practices in data engineering.