Microsoft Data Engineer 

Ireland, Dublin 

176982229

Basic Qualifications:

• Experience in a Data Engineer or Software Engineer role with a focus on cloud-based big data processing.
• Experience in developing tools and data pipelines using Apache Spark and Python or similar tools.
• Experience in building and optimizing "big data" workflows using modern cloud-based platforms, including ETL, business intelligence pipelines, and data visualization tools like Power BI.
• Strong understanding in data modeling.

Preferred Qualifications:

• Experience with one of the major cloud-based data platforms.
• Familiarity with relational databases and working knowledge of a variety of big data sources in Spark, Scala, and/or other big data systems.
• Experience in designing/implementing large-scale data infrastructure to support a Data Science team.
• Demonstrated proficiency in writing complex, highly optimized queries across diverse data sets and implementing data science applications in Python using cloud-based tools.
• Excellent written and verbal communication skills.
  

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.

• Design, develop, maintain, and oversee data infrastructure and back-end services for ML experimentation, investigations, reporting, data collection, and related functions.
• Ensure the quality control of data pipelines and promote best data engineering practices.
• Create and manage reports and dashboards to monitor KPIs, the identity attack ecosystem, and other indicators crucial for understanding the threat landscape and assessing the accuracy and performance of our detections.
• Collaborate with the team to address business inquiries using telemetry data. Effectively communicate key insights and results to stakeholders and leadership. Utilize data storytelling and visualization techniques to recommend product decisions.