Software Engineer II

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Does pioneering new and innovative ways to collect and showcase key customer data sound exciting to you? Are you passionate about data and do you feel we have been missing the opportunity to be more data-informed at Microsoft? Do you want to contribute to an effort that is one of the most critical for the future success of Microsoft, E+D and SCI? If so, the Insights, Data Engineering & Analytics (IDEAs) team might be an excellent place for you to grow your career. M365 together with SCI is at the core of our Company’s mission to enable people and organizations to achieve more. Be part of the team building platform services handling millions of users and exabytes of data. This is not just some large-scale web service: the implementation ranks among the world’s largest and state of the art distributed systems, spanning across data centers around the world. The Insights, Data Engineering & Analytics team’s goal is to champion a data-informed culture; to inspire and enable the entire E+D organization to make more informed decisions through data. We see this effort as a huge opportunity in providing information to the organization that will improve efficiency, empowerment, and help Microsoft win in the critical cloud business sector.

Required Qualifications:

• Bachelor's Degree in Computer Science or related technical field and 3+ years technical engineering experience
• We are looking to hire Full stack, backend and frontend engineers for multiple roles we have
• Experience in coding in languages including, but not limited to, Java, C#, C, C++, or equivalent experience OR/AND experience with at least one of the following scripting languages: JavaScript, PowerShell, Python, Perl, or Ruby (for data manipulation and automation tasks

Preferred Qualifications:

• Experience working and building distributed cloud services using Azure or related technology stacks
• Experience with Azure Data Factory, Cosmos, Kusto, Spark, Kafka or other big-data related technology stacks
• Experience of software testing/release processes and methodologies
• Proven design and analytical skills, with a strong bias for engineering excellence at scale
• Functional knowledge of cloud computing and online services business models, including business, technical, and operational metrics
• Solid background in data warehouse principles, architecture, design and its implementation at large scale
• Ability to operate effectively and independently in a dynamic, fluid environment
• Ability to learn and grasp concepts quickly in a fast-paced environment

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.

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As a Software Engineer II on our team, you would be responsible for:

• The technical leadership and end-to-end development of the data solutions that will help E+D and SCI gain the strategic insights we need to deliver the most optimal user experience and to quickly adapt to market conditions that are constantly evolving
• You will also apply your engineering and analytical skills to petabyte scale data problems using the latest and most modern data analytics technologies on an ever-increasing number of data signals produced by the different products part of the M365 suite and our partners across the company
• In this position you will face tough engineering challenges every day as we deal with very large, disparate and usually complex data sets as we aim to provide an efficient and reliable platform for data wrangling and curation. The integration of different data democratization and visualization techniques will also enable us to extract even the most deeply embedded insights from this data to then make those insights readily available to everyone in our organization, affording them the flexibility of analyzing said data in a self-service manner.