Microsoft Data Engineer II 

United States, Washington 

287579967

Required/Minimum Qualifications

• Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 2+ years 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 AND 1+ years experience in business analytics, data science, data modeling or data engineering work
  • OR equivalent experience.
• 2+ years of experience of building high scale enterprise Business Intelligence and data engineering solutions.
  
• 1+ years of experience in designing and developing distributed systems on cloud platform.
  
• Experience using ML, anomaly detection, predictive analysis, and/or exploratory data analysis.

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.

Additional or Preferred Qualifications

• Experience using a variety of data stores.
• Experience working with large data sets in SQL/Data Bricks/PySparkSQL/Azure Data Factory or similar.
• Experience in Business Intelligence or visualization with tools such as Power BI.
• Demonstrated ability to effectively work and operate in cross-functional global organization.

• Build world class software engineering components and functions.
• Be passionate about technology and obsessed about customer needs.
• Champion data-driven decisions for features identification, prioritization and delivery.
• Deliver on an ambitious product and services roadmap, including building new services on top of vast amount data collected by our batch and near real time data engines.
• Design and architect internet scale and reliable services.
• Leverage ML models knowledge to select appropriate solutions for business objectives.
• Communicate effectively and build relationship with our partner teams and stakeholders.
• Help shape our long-term architecture and technology choices across the full client and services stack.
• Experiment with and recommend new technologies that simplify or improve the tech stack.
• Work to help build an inclusive working environment.