Breakthrough

The Radiology Analytics team is seeking a technically skilled and highly motivated professional to help design, build, and advance the data and analytics ecosystem supporting the Department of Radiology. This role will focus on developing reliable, high-performance data pipelines and platforms that transform complex clinical and operational data into trusted, analytics-ready assets. These datasets will support operational insights and advanced reporting, and serve as a foundation for AI and machine learning initiatives, including predictive and capacity-planning use cases. Serving as a critical bridge between IT and Radiology, this position offers a unique opportunity to deliver solutions that directly enhance efficiency, innovation, and patient care.

The successful candidate will design, build, and operate scalable, production-grade data pipelines and integrations that support analytics and machine learning solutions. This role is responsible for developing and maintaining reliable data ingestion, processing, and storage workflows using platforms such as Microsoft Fabric, with a focus on data quality, performance, and operational stability. The position requires a strong understanding of enterprise data architectures and tooling, along with the ability to exercise independent technical judgment. The role will collaborate with data scientists, data analysts, and IT partners to engineer clinical and operational data into trusted, analytics- and model-ready datasets that support advanced analytics, AI development, and data-driven decision-making across Radiology. 

May be required to provide 24/7 call support.   

During the selection process you may participate in an OnDemand (pre-recorded) interview that you can complete at your convenience. During the OnDemand interview, a question will appear on your screen, and you will have time to consider each question before responding. You will have the opportunity to re-record your answer to each question – Mayo Clinic will only see the final recording. The complete interview will be reviewed by a Mayo Clinic staff member and you will be notified of next steps.

A Codility exam will be required as part of the interview screening process for this position.  

This vacancy is not eligible for sponsorship/we will not sponsor or transfer visas for this position. Also, Mayo Clinic DOES NOT participate in the F-1 STEM OPT extension program.

A Bachelor's degree in a relevant field such as engineering, mathematics, computer science, information technology, health science, or other analytical/quantitative field and a minimum of five years of professional or research experience in data visualization, data engineering, analytical modeling techniques; OR an Associate’s degree in a relevant field such as engineering, mathematics, computer science, information technology, health science, or other analytical/quantitative field and a minimum of seven years of professional or research experience in data visualization, data engineering, analytical modeling techniques. In-depth business or practice knowledge will also be considered.

Incumbent must have the ability to manage a varied workload of projects with multiple priorities and stay current on healthcare trends and enterprise changes. Interpersonal skills, time management skills, and demonstrated experience working on cross functional teams are required. 

Requires strong analytical skills and the ability to identify and recommend solutions and a commitment to customer service. 

The position requires excellent verbal and written communication skills, attention to detail, and a high capacity for learning and problem resolution.

Advanced experience in SQL is required. Strong Experience in scripting languages such as Python, JavaScript, PHP, C++ or Java & API integration is required. Experience in hybrid data processing methods (batch and streaming) such as Apache Spark, Hive, Pig, Kafka is required. Experience with big data, statistics, and machine learning is required. 

The ability to navigate linux and windows operating systems is required. 

Knowledge of workflow scheduling (Apache Airflow Google Composer), Infrastructure as code (Kubernetes, Docker) CI/CD (Jenkins, Github Actions) is preferred. Experience in DataOps/DevOps and agile methodologies is preferred. 

Experience with hybrid data virtualization such as Denodo is preferred. 

Working knowledge of Tableau, Power BI, SAS, ThoughtSpot, DASH, d3, React, Snowflake, SSIS, and Google Big Query is preferred. 

License or Certification:
Google Cloud Platform (GCP) certification is preferred.