Group Engineering Manager at Microsoft

Group Engineering Manager Details

April 23, 2019, 9:15 p.m.
Engineering
People Manager
Full-Time
Redmond, WA
and Analytics team Microsoft? Do you
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've 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 M365 and E+D? If so, the Microsoft 365 Insights, Data Engineering and Analytics team might be an excellent place for you to grow your career. M365 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 Microsoft 365 Insights, Data Engineering and Analytics team's goal is to champion a data-informed culture; to inspire and enable the entire E+D organization

We are looking for a Group Engineering Manager who is deeply passionate about building services at scale and championing a data-informed culture across E+D. You will lead and grow a engineering team, which is responsible for growing the business via ML models and customer surfaces as well as of course improving and scaling out the service. This role will work closely with the data science team, data analytics, program management and design to deliver powerful but delightful experiences to our users. The team will need to pursue ambiguous problems, be agile in order to adapt to timelines, iteratively
Master's degree required; MSCS or higher strongly preferred. At least 12 years' experience in software engineering, programming or development. Software programming experience in C#, Java, or C++. Experience with Azure Data Factory, Azure SQL Data Warehouse, DataBricks, Cosmos, Kusto and other big-data related technology stacks. Experience with machine learning techniques and tools Experience with data analytics and visualizations (e.g., Power BI, Azure Analysis Services, Interana, etc.). Familiarity with data analysis tools and statistical packages, such as R, MATLAB, and Python's Pandas. Prior
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