Microsoft Data Engineer 

Austria 

435226267

As a Data Engineer, you will learn a lot about how our ambient speech healthcare AI product works. You will join our dedicated Data Engineering team to securely deliver, curate and manage high quality data that enables Healthcare research projects, whilst also meeting high standards for security and data governance.

Minimum Requirements

• programming skills in languages including, but not limited to Python
• Multi-year technical experience developing big data management solutions as a data engineer
• Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND multi-year 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 multi-year experience in business analytics, data science, software development,or data engineering work OR equivalent experience

Preferred/Additional Qualifications (Optional, at HM discretion)

• Multi-year technical experience working with relational databases and query languages
• Previous experience managing software DevOps (especially ADO pipelines)
• Experience with Azure ecosystem including cross tenants and highly restricted environments, as well as developing scalable processing using Spark in Python especially in Azure will be considered strong assets
• Experience complying with data governance and compliance standards such as GDPR or HIPAA within restricted environments
• Experience developing and deploying dashboards (especially in Power BI)

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.

The salary for this role is starting from 66,900 euros per annum depending on experience.

Responsibilities include:

• Develop, deploy and monitor scalable data pipelines that ingest and process data from
multi-tenant production environments to research environments using Python/Spark .
• Develop, deploy and monitor data enrichment workflows including dataset creation,
cataloging and reporting.
• Develop and deploy tooling that ensures compliance with data governance and life cycle
management requirements and best practices.
• Detect, monitor, and resolve data quality issues in collaboration with other teams.
• Implement tools and data architecture improvements that increase data usability and quality.