Do you have a relentless passion for data engineering and analytics and a desire to drive future products via key data insights? Does the thought of being able to influence the product in each stage of the lifecycle through data engineering, platforms & insights it powers, excite you? Do you love designing, measuring, understanding, and visualizing based on real-world user data to come up with insights that drive experiments and recommendations to help move business metrics? If so, we want to talk to you!
We are the CIX Data team, part of the Windows and Devices (W+D) engineering organization. Our goal is to use advanced data engineering, analytics & data science to inform decision making, drive product performance and maximize business impact through the power of ML/AI. In short, we thrive on data to solve high impact business problems to enhance the experiences of Microsoft consumers! We are looking for a strong Data Engineer who can help us power and foster a data-driven culture here in CIX(Consumer Identity Experiences)!
We're looking for an enthusiastic and expert Software & Data Engineers to help us build and deliver business Intelligence through data for experiences across 1.5 billion Windows devices and various Microsoft products. Your responsibilities will include working closely with a variety of teams such as Engineering, Program Management, Design and application partners to understand the key business questions for customer-facing scenarios, to set up the key performance indicators, and setup data pipelines to identify insights and experiment ideas that moves our business metrics. We will be looking to you to help evaluate the return of investments on new ideas, to assess if investments are meeting customer and business promises, to design and assess experiments, to measure growth and to derive insights that help identify next wave of opportunities and problems to be solved.
Basic Qualifications:
- 7+ years of experience in engineering
- Proven coding and debugging skills in C#, C++, Java, or SQL
- Ability to work and communicate effectively across disciplines and teams
- Familiarity with distributed data processing and analysis, such as Map-Reduce or Apache Spark.
- BS or MS degree in Computer Science or Engineering OR equivalent years of work experience.
Preferred Qualifications:
- 5+ years of experience in data engineering
- Understanding and experience with data cloud computing technologies such as – Azure Synapse, Azure Data Factory, SQL, Azure Data Explorer, Power BI, PowerApps, Hadoop, YARN, Apache Spark
- Excellent analytical skills with systematic and structured approach to software design
#data science
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.
Responsibilities
- Enable the Windows, Developers, and Experiences team to do more with data across all aspects of the development lifecycle.
- Contribute to a data-driven culture as well as a culture of experimentation across the organization.
- Provide new and improve upon existing data platform offerings with a fundamental understanding of the end-to-end scenarios.
- Collaborate with partner teams and customers to scope and deliver projects.
- Authoring and design of Big Data ETL pipelines in SCOPE, Scala, SQL, Python, or C#
- Data extraction across a wide variety of data sources
- Data cleaning, preprocessing, and transformation for further analysis by data analysts
- Data Validation framework from source to endpoints ensuring data quality and integrity
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