Microsoft Data Engineer 

Austria, Vienna, Vienna 

698106057

achieve their goals and improve patient care. We aim to create an efficient and connected healthcareecosystem by bringing the healthcare ecosystem together which empowers everyone across thefor their workforces and patients or members alike.

training, fine-tuning, and evaluating AI models.

Required/Minimum Qualifications:

• Bachelor’s Degree in Computer Science, Math, Software Engineering, Computer Engineering,or related field AND experience in business analytics, data science, software
  development, data modeling or data engineering work
• OR Master’s Degree in Computer Science, Math, Software Engineering, Computer Engineeringor related field AND experience in business analytics, data science, software
  development, or data engineering workOR equivalent experiencetechnical engineering experience with coding in languages including, but not limited
  to, Pythontechnical experience working with query languages

Preferred/Additional Qualifications:

• technical experience working as a data engineer
• technical experience working with relational databases and query languages
• Experience with Azure ecosystem
• Experience with data governance and compliance standards such as GDPR or HIPAA
• Experience working together with ML researchers
• Good communication, collaboration, and problem-solving skills
• Initiative, big-picture mindset and focus on collaboration and team vs. personal recognition
• Knowledge about EU data privacy (GDPR) and/or de-identification

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 everytwo years thereafter.

The salary for this role is starting from 59,000 euros per annum depending on experience.

Responsibilities include:

• Work with researchers to help experts create and annotate data for training, tuning, and evaluatingAI models
• Organize and distribute data for annotation
• Assist annotators by developing data tools to validate annotations and provide analysis and
  Inter-Annotator Agreement (IAA) reports to measure quality of annotation.
• Extract, validate, and catalog data that has been annotated, following data stewardship andcompliance processes
• Continuously communicate and triage to determine priorities with stakeholders and execute themost impactful
• Apply good coding standards and patterns and advocate for best practices in data engineering