Microsoft Data Engineer 

Austria 

154781749

As a Data Engineer, you will learn a lot about how our ambient speech healthcare AI product works both from an end user's perspective as well as from a technical perspective (especially the data architecture). You will help us improve our products aiming to reduce healthcare clinician burnout and to improve the patient experience. You will get to know many of the teams involved in developing the project, and improve your data engineering skills alongside other experienced engineers and data scientists in a very fast moving and modern hybrid work environment, where working from home most days of the week is fine.

Required/Minimum Qualifications

• Bachelor’s or master’s degree in computer science, math, software engineering, computer engineering, or related field (or equivalent experience) AND multi-year experience in business analytics, data science, software development, data modeling or data engineering work
• Strong Python development skills, OR very strong skills in another programming language with demonstratable ability to learn Python very quickly
• Experience with relational databases, query languages and data modelling

Preferred/Additional Qualifications

• Multi-year experience working as a data engineer using PySpark
• Experience with Azure ecosystem
• Experience with data governance and compliance standards such as GDPR or HIPAA
• Experience with data analysis, visualizations, and dashboards (especially in Power BI)
• Good communication, collaboration, and problem-solving skills

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 66,900 euros per annum depending on experience.

• Develop and maintain scalable data pipelines using Python/Spark/SQL
• Detect, monitor, and resolve data quality issues together with other teams
• Make it easier for consumers downstream to make best use of the available data
• Work with producers upstream to ensure we collect the data we need