Data Engineer

Microsoft’s Health and Life Sciences team is dedicated to empowering healthcare organizations to achieve their goals and improve patient care. We aim to create an efficient and connected healthcare ecosystem by bringing the healthcare ecosystem together which empowers everyone across the healthcare journey to collaborate, communicate, and innovate together to provide better experiences for their workforces and patients or members alike.

Our team has an exciting opportunity to be a Data Engineer on the cutting edge of AI Research and Development! Work with Researchers and Medical Subject Matter Experts to create data sets for training, fine-tuning, and evaluating AI models.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

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 Engineering or related field AND experience in business analytics, data science, software
  development, or data engineering work OR equivalent experience technical engineering experience with coding in languages including, but not limited
  to, Python technical 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 every two years thereafter.

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

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 include:

• Work with researchers to help experts create and annotate data for training, tuning, and evaluating AI 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 and compliance processes
• Continuously communicate and triage to determine priorities with stakeholders and execute the most impactful
• Apply good coding standards and patterns and advocate for best practices in data engineering