Job Description

Microsoft runs on trust. As our lives and businesses are becoming increasingly digitized, trust is the glue that holds our world together. To create and enhance this trust, we must proactively protect our customers, partners, and Microsoft from operational risk.

The 3rd Party Compliance Engineering team subscribes to a 'lean startup' culture in shipping modern, customer-centric, data driven products that offer unparalleled levels of risk protection. We embrace collaboration, agility, and the belief that experimentation (failing fast) drives innovation. In our daily work, we demonstrate growth mindset, ownership, grit, vision, curiosity, and courage; we require you to bring those values as well. When you join this award-winning team, you will become a member of a diverse, and inclusive cohort of extremely talented engineers-- each of whom love sharing knowledge, have big hearts, and small egos. You will work and learn from experts across domains that include cloud architecture, distributed systems, business process automation, AI/ML, cybersecurity, digital fingerprinting, philanthropy, and operations. When surveyed anonymously, 100% of our team agreed that their roles had real purpose, and their job was more than just a job.

Now let us talk about you. We are looking for a talented Data Software Engineer to help us design and support cloud native data solutions that enables our org and customers to effectively monitor, analyze, and make better data-driven decisions on their business. You enjoy data optimization, discovering hidden patterns in data and applying analytical techniques to answer a wide range of high-impact business questions. You have passion and desire to work under an Agile DevOps culture and you enjoy the rhythm of a fast-paced startup environment. You relish the opportunity to create world-impacting data solutions that most people would not believe are possible, and yet you also feel motivated when contributing in small ways. If this sounds like you, and you buy into our team's values, then come help us build a foundation of trust for our world's digital future.

* Design, develop, and maintain data pipelines for real-time/batch analysis, reporting, optimization, data collection, and related functions.
* Build and maintain data processing infrastructure that support complex analysis across our data science, product, and experimentation teams.
* Use large data sets to resolve major business and functional issues while improving data reliability, efficiency, and quality.
* Collaborate with colleagues including product owners, data scientists and other engineers to identify a business or engineering problem and translate it to a data science problem, dig out sources of data, conduct the analysis that would reveal useful insights, and help product teams to operationalize the solution.
* Continuous learning and working closely with the latest technologies (AI/ML, Cloud Lakehouse/Synapse Analytics, etc.) in Microsoft.u202F

Required qalifications:

* A minimum of a bachelor's degree in Machine Learning/Data Science, Applied Statistics, Mathematics, Engineering or a related field, or equivalent alternative education, skills, and/or practical experience.
* At least 3 years' experience using large data systems (Big Data) and building databases, ETL, and reporting solutions.

Preferred qualifications:

* Solid understanding of Cloud centric data approach including SQL and NoSQL databases (ex. Azure SQL, Azure Cosmos DB).
* Proficiency in writing complex, highly optimized queries across large data sets.
* Experience working with Data Lake, Data Factory, Databricks or Apache Spark.
* Experience deploying cloud-based data services, including data pipeline orchestration using Infrastructure as Code (IaC).
* Experience with C, SQL, Scala/Python/Java, T-SQL or similar scripting language.
* Exposure to Agile software delivery and modern DevOps practices (including Git, CI/CD).
* Data visualization and dashboard design experience is a plus but not required.